JP2014503796A - Wide-area positioning system - Google Patents

Abstract

  The positioning system and positioning method includes a network of transmitters that broadcast positioning signals including ranging signals and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. A reference sensor array including at least one reference sensor unit is positioned at a known location. The remote receiver includes an atmospheric sensor that collects atmospheric data at the location of the remote receiver. A positioning application is coupled to the remote receiver and uses the atmospheric data and reference data from the reference sensor array to generate a reference pressure estimate at the location of the remote receiver. The positioning application uses the reference pressure estimate and information derived from at least one of the positioning signal and a satellite signal that is a signal of a satellite-based positioning system to calculate the position of the remote receiver. The location can include elevation.

Description

RELATED APPLICATION This application claims the benefit of US patent application Ser. No. 61 / 413,170, filed Nov. 12, 2010.

  This application is a continuation-in-part of US patent application Ser. No. 12 / 557,479, filed on Sep. 10, 2009.

  The present disclosure relates generally to positioning systems. Specifically, the present disclosure relates to a wide area positioning system.

  Positioning systems such as the Global Positioning System (GPS) have been used for many years. However, in poor signal conditions, these conventional positioning systems can have degraded performance.

  Examples of the present application disclose, for example, a wide-area positioning system.

  Examples of the present application disclose, for example, a wide-area positioning system.

1 is a block diagram illustrating a wide area positioning system, under an embodiment. FIG. FIG. 3 is a block diagram illustrating synchronized beacons, under an embodiment. FIG. 2 is a block diagram illustrating a positioning system using a repeater configuration, under an embodiment. FIG. 6 is a block diagram illustrating a positioning system using a repeater configuration under an alternative embodiment. FIG. 6 illustrates tower synchronization, under an embodiment. 2 is a block diagram illustrating a GPS-controlled PPS generator, under an embodiment. FIG. FIG. 2 illustrates a GPS controlled oscillator, under an embodiment. FIG. 4 is a signal diagram that counts the time difference between a PPS and a signal that allows an analog section of a transmitter to transmit data, under an embodiment. 1 is a block diagram illustrating a differential WAPS system, under an embodiment. FIG. FIG. 6 is a diagram illustrating common view time transfer under an embodiment. FIG. 6 illustrates a bidirectional time transfer under an embodiment. FIG. 2 is a block diagram illustrating a receiver unit, under an embodiment. FIG. 2 is a block diagram illustrating an RF module, under an embodiment. FIG. 6 illustrates signal up-conversion and / or signal down-conversion, under an embodiment. FIG. 3 is a block diagram illustrating a receiver system having multiple receive chains that can be temporarily used to receive and process a WAPS signal, under one embodiment. FIG. 3 is a block diagram illustrating clock sharing in a positioning system, under an embodiment. FIG. 4 is a block diagram illustrating assistance transfer from a WAPS receiver to a GNSS receiver, under an embodiment. FIG. 3 is a block diagram illustrating the transfer of aiding information from a GNSS receiver to a WAPS receiver, under an embodiment. It is a figure which shows the structure of the example in which WAPS assistance information is provided from a WAPS server under one Embodiment. 6 is a flow diagram for estimating the earliest arriving path in h [n], under an embodiment. 3 is a flow diagram for estimation of a reference correlation function, under an embodiment. 2 is a flow diagram for noise subspace estimation, under an embodiment. 6 is a flow diagram for noise subspace estimation under an alternative embodiment. 6 is a flow diagram for noise subspace estimation under another alternative embodiment. 6 is a flow diagram for noise subspace estimation under another alternative embodiment. 6 is a flow diagram for noise subspace estimation under another alternative embodiment. FIG. 2 is a block diagram illustrating a reference elevation pressure system, under an embodiment. FIG. 2 is a block diagram illustrating a WAPS integrating a reference elevation pressure system, under an embodiment. FIG. 2 is a block diagram illustrating hybrid position estimation using distance measurements from various systems, under an embodiment. FIG. 3 is a block diagram illustrating hybrid position estimation using position estimates from various systems, under an embodiment. FIG. 3 is a block diagram illustrating hybrid position estimation using a combination of distance estimates and position estimates from various systems, under an embodiment. Position / velocity estimates from the WAPS / GNSS system to help calibrate the drifting bias of the sensor when the quality of the GNSS / WAPS position and / or velocity estimates is good, under an embodiment 5 is a flowchart relating to determination of a hybrid position solution in which is fed back. Under one embodiment of a hybrid position solution where sensor parameters (bias, scale, drift, etc.) are estimated as part of the position / velocity calculation within the GNSS unit and / or WAPS unit without the need for explicit feedback It is a flowchart regarding determination. 2 is a flow diagram for determining a hybrid position solution in which sensor calibration is separated from individual position calculation units, under an embodiment. 6 is a flow diagram for determining hybrid position solutions in which sensor parameter estimation is performed as part of the state of individual position calculation units, under an embodiment. FIG. 2 is a diagram illustrating the exchange of information between a WAPS system and another system, under an embodiment. FIG. 3 is a block diagram illustrating the exchange of location estimates, frequency estimates, and time estimates between an FM receiver and a WAPS receiver, under an embodiment. FIG. 4 is a block diagram illustrating the exchange of location estimates, time estimates, and frequency estimates between a WLAN / BT transceiver and a WAPS receiver, under an embodiment. FIG. 3 is a block diagram illustrating the exchange of location estimates, time estimates, and frequency estimates between a cellular transceiver and a WAPS receiver, under an embodiment. FIG. 2 illustrates a parallel complex correlator architecture, under an embodiment. FIG. 3 illustrates a 32-bit shift register implementation derived from two 16-bit shift register primitives with parallel random access read capabilities, under an embodiment. FIG. 6 is a diagram illustrating a shift operation and a read operation rate according to an embodiment. FIG. 3 illustrates the structure of an adder tree that implements a 1023 × n-bit adder, under an embodiment. FIG. 3 is a block diagram illustrating session key setup, under an embodiment. 3 is a flow diagram for encryption, under an embodiment. FIG. 2 is a block diagram illustrating a security architecture for encryption, under an alternative embodiment.

  A system and method for determining the position of a receiver is described. The positioning system of an embodiment includes a transmitter network that includes a transmitter that broadcasts a positioning signal. The positioning system includes a remote receiver that acquires and tracks positioning signals and / or satellite signals. The satellite signal is a signal of a satellite-based positioning system. The first mode of the remote receiver uses terminal-based positioning where the remote receiver calculates the position using positioning signals and / or satellite signals. The positioning system includes a server coupled to the remote receiver. The second mode of operation of the remote receiver includes network-based positioning in which the server calculates the position of the remote receiver from the positioning signal and / or satellite signal, where the remote receiver is a positioning signal and / or satellite signal. Is transferred to the server.

  The method of determining the position of an embodiment includes receiving at least one of a positioning signal and a satellite signal at a remote receiver. The positioning signal is received from a transmitter network that includes a plurality of transmitters. The satellite signal is received from a satellite based positioning system. The method includes determining the location of the remote receiver using one of terminal-based positioning and network-based positioning. Terminal-based positioning includes calculating the position of the remote receiver at the remote receiver using at least one of the positioning signal and the satellite signal. Network-based positioning includes calculating the position of a remote receiver at a remote server using at least one of a positioning signal and a satellite signal.

  In the following description, numerous specific details are introduced to provide a thorough understanding and enable the description of the described systems and methods. However, one of ordinary skill in the art appreciates that these embodiments can be practiced without one or more of the specific details or with other components, systems, and the like. In other instances, well-known structures or operations are not shown or described in detail to avoid obscuring aspects of the disclosed embodiments.

  FIG. 1 is a block diagram of a positioning system, under an embodiment. A positioning system, also referred to herein as a global positioning system (WAPS) or “system”, acquires and tracks a network of synchronized beacons and beacon and / or global positioning system (GPS) satellites (and A receiver unit (optionally including a location calculation engine) and a server including a tower index, a billing interface, a proprietary encryption algorithm (and optionally a location calculation engine). The system operates in a licensed / unlicensed band of motion and transmits proprietary waveforms for location and navigation. The WAPS system can be used in conjunction with other positioning systems for better location resolution, or the WAPS system can be used to assist other positioning systems. In the context of this document, a positioning system is a system that localizes one or more of latitude, longitude, and altitude coordinates.

  In this document, whenever reference is made to “GPS”, this may include other existing satellite positioning systems such as Glonass and future positioning systems such as Galileo and Compass / Beidou, GNSS (Global Navigation It is referred to broadly in the sense of satellite system.

  FIG. 2 is a block diagram of a synchronized beacon, under an embodiment. The synchronized beacons of one embodiment, also referred to herein as beacons, form a CDMA network, each beacon embedded with a pseudo-random number (PRN) sequence having good cross-correlation characteristics such as a Gold code. Send along with the data stream of assistance data. Alternatively, the sequences from each beacon transmitter can be staggered over time in separate slots in the TDMA format.

  In terrestrial positioning systems, one of the major challenges to overcome is the perspective problem at the receiver, where distant transmitters are obstructed by nearby transmitters. To address this issue, the beacon of one embodiment is a CDMA technique that allows local transmitters to use separate slots (TDMA) (and optionally different codes (CDMA)) to mitigate perspective problems, and Use a combination of TDMA techniques. Further distant transmitters are allowed to use the same TDMA slot while using different CDMA codes. This allows for wide-area scalability of the system. TDMA slotting can be critical for guaranteed perspective performance or can be randomized to provide good average perspective performance. The carrier signal can also be offset by a certain number of Hertz (eg, a fraction of the Gold code repetition frequency) to improve code cross-correlation performance to address all “far and near” problems. When two towers use the same TDMA slot but with different signs, they may further reject cross-correlation at the receiver by using stronger signal interference cancellation before detecting weaker signals. it can.

  Another important parameter of a TDMA system is the TDMA slotting period (also referred to as a TDMA frame). Specifically, in a WAPS system, the TDMA frame duration is the time period between two consecutive slots of the same transmitter. The TDMA frame duration is determined by the product of the number of transmission slots required for positioning within the coverage area and the TDMA slot duration. Although TDMA slot duration is determined by sensitivity requirements, sensitivity is not necessarily limited by a single TDMA slot. One example configuration may use 1 second as the TDMA frame duration and 100 ms as the TDMA slot duration.

  In addition, the beacon of an embodiment can use a preamble that includes assistance data, or it can use information for channel estimation and forward error detection and / or correction to help make the data robust. Can be used. The assistance data of one embodiment includes the exact system time of either the rising or falling edge of the waveform pulse, the tower geocode data (latitude, longitude, and altitude), and the adjacent tower geocode information and area. Index of sequences used by various transmitters within, transmitter (optional) and clock timing correction of adjacent transmitters, local atmospheric correction (optional), and relationship of WAPS timing to GNSS time (optional) One or more of: an indication of urban, sub-urban, countryside (optional) to help the receiver with pseudo-range resolution, and an offset from the base index of the PN sequence or an index to the Gold code sequence Including, but this But it is not limited. Within a broadcast transmitted data frame, a field may be included that contains information that disables a single receiver or set of receivers for security and / or license management reasons.

  The transmit waveform timings of transmissions from different beacons and towers in one embodiment are synchronized to a common timing reference. In the alternative, the timing difference between transmissions from different towers is known and must be transmitted. Assistance data is repeated at intervals determined by the number and size of data blocks, except for timing messages that are incremented at regular intervals. Assistance data can be encrypted using a proprietary encryption algorithm, as described in detail herein. The spreading code can also be encrypted for additional security. The signal is upconverted and broadcast on a predefined frequency. The end-to-end delay in the transmitter is accurately calibrated to ensure that the differential delay between beacons is less than about 3 nanoseconds. By using a differential WAPS receiver at the investigated location listening for a set of transmitters, a relative clock correction for the transmitters in that set can be found.

The tower arrangement in one embodiment is optimized for coverage and location accuracy. Tower deployments are arranged to receive signals from more than two towers at most of the locations in the network and at the edge of the network, and geometric accuracy of precision (GDOP) at each of these locations. ) Is below a predetermined threshold based on accuracy requirements. Software programs that perform RF planning studies are augmented to include analysis on GDOP in and around the network. GDOP is a function of receiver position and transmitter position. One way to incorporate GDOP into network planning is to set up optimization as follows. The function to minimize is the volume integral of the square of GDOP over the coverage volume. Volume integration relates to the (x, y, z) coordinates of the receiver position. The minimization is in a given coverage area and is constrained to be in the coverage volume n transmitter position coordinates (x ₁ , y ₁ , z ₁ ), (x ₂ , y ₂ , z ₂ ),... (X _n , y _n , z _n ), ie, for i = 1,..., N, x _min <x <x _max , y _min <y <y _max , z _min <z <z _max X _min , y _min , and z _min are the lower limits of the coverage volume, and x _max , y _max , and z _max are the upper limits of the coverage volume. The function to be minimized is

Can be written.

Furthermore, the function to be minimized can be weighted according to the importance of the coverage region R _j (ie, the required performance quality).

Additional constraints on the tower coordinate location may be based on the locations of already available towers within a given area. Coordinating all coordinates can usually be done in a local level coordinate system with mean east as positive x, mean north as positive y, and mean vertical on positive z. The software that solves the constrained minimization problem above optimizes the transmitter location (x ₁ , y ₁ , z ₁ ), (x ₂ , y ₂ , z ₂ ),... (X _n , y _n , z _n ).

  This technique can be applied for both wide area networks (such as in a city) or local deployments (such as in a mall). In one example configuration, the transmitter networks are separated by a distance of about 30 km in a triangular / hexagonal arrangement around each metropolitan area. Each tower can radiate via a corresponding antenna up to a maximum power in the range of about 20 W to 1 kW EIRP. In another embodiment, the tower can be localized and can transmit at power levels as low as 1W. The frequency band of operation includes any licensed or unlicensed band in the radio spectrum. The transmit antenna of one embodiment includes an omni-directional antenna or multiple antennas / arrays that can assist with diversity, sectoring, etc.

  Adjacent towers are differentiated by using different sequences with good cross-correlation properties to be transmitted, or alternatively to transmit the same sequence at different times. These differentiation techniques can be combined and applied only to a given geographic area. For example, the same sequence can be reused across networks in different geographic areas.

  Local towers can be placed within a given geographic area to augment the wide area network tower of one embodiment. Local towers can improve positioning accuracy when used. Local towers can be deployed within a campus-like environment or can be separated by distances ranging from 20-30 meters to 2-3 kilometers for public safety needs.

  The towers are preferably placed at various heights (rather than similar heights) to facilitate better quality altitude estimation from the position solution. In addition to different latitude / longitude transmitters with different heights, another way to add height diversity to a tower is to add multiple to different heights of the same physical tower (having the same latitude and longitude). Having a WAPS transmitter (using a different code sequence). Note that different code sequences on the same physical tower can use the same slot because transmitters on the same tower do not cause perspective problems.

  The WAPS transmitter can be located in an existing tower or a new tower (such as a cellular tower) used for one or more other systems. The WAPS transmitter deployment cost can be minimized by sharing the same physical tower or location.

  To improve performance in a localized area (eg, warehouse or mall), additional towers can be placed in that area to augment transmitters used for wide area coverage. Alternatively, repeaters can be placed in the area to reduce the cost of installing all transmitters.

  The transmission beacon signal used for the positioning mentioned above does not need to be a transmitter made exclusively for WAPS, but any other system that is initially synchronized in time or related to it Note that synchronization can be a signal from a system that is augmented via an additional timing module. Alternatively, this signal can be from a system whose relative synchronization can be determined via a reference receiver. This system can be, for example, already deployed or newly deployed with additional synchronization capabilities. An example of such a system may be a broadcast system such as digital TV, analog TV, or MediaFlo.

  When a WAPS network is configured, some transmission locations may be better than some other location in the network (beacon height above the clutter, as determined by either design or field measurements). Power level). Either such a beacon, directly or indirectly, or by encoding a data bit that indicates the “quality” of the beacon that the receiver can use to weight the signal received from such beacon. Can be identified to the receiver.

  FIG. 3 is a block diagram of a positioning system that uses a repeater configuration, under an embodiment. The repeater configuration includes the following components:

1) Common WAPS receiving antenna (antenna 1)
2) Splitter / switch connections to RF power amplifiers and various WAPS transmitter antennas (local antennas 1-4).

3) WAPS user receiver The antenna 1 receives the composite signal, amplifies it, and distributes (switches) it to the local antennas 1 to 4. The switching should be done in a way that (preferably) there is no overlap of transmissions from different repeaters at the user receiver. Transmission collisions can be avoided through the use of guard intervals. The known cable delay from the switch to the transmit antenna is either due to the sum of the repeater-amplifier-transmitter delay or the user-receiver cable delay to equalize the overall delay for all local repeaters. It must be compensated either by adjusting the estimated time of arrival from a particular repeater. When TDMA is used in a wide area WAPS network, the repeater slot switching rate is selected such that each wide area slot (each slot includes one wide area WAPS tower) occurs in all repeater slots. One example configuration uses a repeater slot duration equal to a multiple of the global TDMA frame duration. Specifically, if the wide area TDMA frame is 1 second, the repeater slot can be an integer number of seconds. This configuration is the simplest, but is only suitable for deployment in small confined areas due to the requirement of RF signal distribution on the cable. The user WAPS receiver uses the arrival time difference when listening to the repeater tower to calculate the position and works under static (or quasi-static) assumptions during repeat tasting. The fact that the transmission is from a repeater can be automatically detected by the fact that each WAPS tower signal exhibits the same timing difference (jump) from one repeater slot to the next.

  FIG. 4 is a block diagram of a positioning system using a repeater configuration, under an alternative embodiment. In this configuration, each repeater includes a WAPS repeater-receiver and an associated coverage-enhanced WAPS transmitter with a local antenna (eg, can be indoors). The WAPS repeater receiver must be able to extract the WAPS system timing information as well as the WAPS data stream corresponding to one wide area WAPS transmitter. The data corresponding to the WAPS system timing and one wide area WAPS transmitter is passed to the corresponding local area WAPS transmitter, which can retransmit the WAPS signal (eg, different codes and Using the same slot). The transmitter includes additional data in its transmission, such as the latitude, longitude, and altitude of the local antenna. In this configuration, the WAPS user receiver operation (distance measurement and position measurement) can be transparent to the fact that the signal is coming from the repeater. Note that the transmitter used in the repeater is cheaper than a full WAPS beacon in that it does not need to have a GNSS timing unit to extract GNSS timing.

  Depending on the mode of operation of the receiver unit, either terminal-based positioning or network-based positioning is provided by the system. In terminal-based positioning, the receiver unit calculates the user's position on the receiver itself. This is useful in applications such as turn-by-turn direction, geo-fencing, etc. In network-based positioning, the receiver unit receives signals from the tower and communicates or transmits the received signals to a server to calculate the user's location. This is useful in applications such as E911 and asset tracking and management with centralized servers. Server location calculations can be post-processed in near real time or with data from multiple sources (eg, GNSS, differential WAPS, etc.) to improve accuracy at the server. The WAPS receiver can also provide and obtain information from a server (eg, similar to SUPL Secure User Plane) to facilitate network-based positioning.

  The towers of the embodiments autonomously maintain synchronization with each other or use network-based synchronization. FIG. 5 illustrates tower synchronization, under an embodiment. The following parameters are used to describe the synchronization aspect.

System transmitter time = t _WAPS-tx
Absolute time reference = t _{WAPS_abs}
Time adjustment = Δ _system = t _WAPS−tx −t _{WAPS_abs}
Note that it is not essential to synchronize the WAPS system time with respect to an absolute time reference. However, all WAPS transmitters are synchronized to a common WAPS system time (ie, relative timing synchronization of all WAPS transmitters). The timing correction of each transmitter relative to the WAPS system time (if present) must be calculated. Timing correction must be made available to the receiver either directly via radio wave WAPS assistance transmission or via some other communication means. Assistance can be delivered to the WAPS receiver via, for example, a cellular (or other) modem or via broadcast data from a system (such as Iridium, Digital TV, MediaFlo, or a cellular system broadcast channel). it can. Alternatively, timing corrections can be sent to the server and used when calculating the position at the server. The description of the tower synchronization of the embodiment is continued here.

  Under network-based synchronization, the towers synchronize with each other within the local area. As described in detail herein, synchronization between towers is generally modulated using pulses (any form of modulation on the carrier for better time resolution, and / or Or spreading using a spreading code, which modulates the carrier) and includes synchronization to pulse edges on the receiver.

  In the autonomous synchronization mode of the embodiment, the towers are synchronized using a local timing reference. The timing reference can be, for example, a GPS receiver, a very accurate clock source (eg, an atomic clock source), a local time source (eg, a GPS controlled clock), and any other network of reliable clock sources Can be one of the following. The use of signals from XM satellite radios, LORAN, eLORAN, TV signals, etc. that are accurately time synchronized can be used as a coarse timing reference for the tower. As an example in one embodiment, FIG. 6 illustrates a PPS pulse source from a GPS receiver used to regulate an accurate / stable timing source, such as a rubidium, cesium, or hydrogen master, under an embodiment. FIG. Alternatively, a GPS controlled rubidium clock oscillator can be used, as shown in FIG.

  Referring to FIG. 6, the time constant of the PLL in the exact clock source is a sufficiently large number (eg, 0.5 to 0.5) that provides better short-term stability (or equivalently, filtering of short-term GPS PPS variation). GPS-PPS provides longer term stability and wide area “coarse” synchronization. The transmitter system continuously monitors these two PPS pulses (from the GPS unit and the exact clock source) and reports any anomalies. An anomaly is that after two PPS sources are locked for several hours, one of the PPS sources drifts away from the other source by a given time threshold determined by the tower network administrator. There is a possibility. A third local clock source can be used to detect anomalies. In the case of abnormal behavior, a PPS signal that exhibits the correct behavior is selected by the transmitter system and reported back to the monitoring station. In addition, whether the instantaneous time difference (reported by the time source) between the PPS input and the PPS output of the exact time source is broadcast by the transmitter or sent to the server used when post processing Can do either.

  In the transmitter system, the time difference between the rising edge of the PPS pulse input and the rising edge of the signal that allows the analog section of the transmitter to transmit data is measured using an internally generated high-speed clock. Is done. FIG. 8 is a signal diagram that counts the time difference between the PPS and a signal that allows the analog section of the transmitter to transmit data, under an embodiment. A count representing the difference is sent to each of the receivers as part of the data stream. The use of a very stable clock reference, such as a rubidium clock (the clock is stable over time / day), allows the system to tower on the device if the device cannot further modulate the specific tower data. This correction can be stored / transmitted every time. This correction data can also be sent to the device via the communication medium if there is something available. The correction data from the tower can be monitored by either a reference receiver or a receiver mounted on the tower listening for other tower broadcasts and can be communicated to a centralized server. Towers can also periodically send this count information to a centralized server that can subsequently disseminate this information to devices near those towers via communication links to the devices. Alternatively, the server can pass information from the tower (eg, on-site) to the adjacent tower to allow this information to be broadcast as assistance information for the adjacent tower. . Assistance information for adjacent towers can include location information (because the tower is static) and timing correction information for nearby towers.

  Similar to the transmitter timing correction of one embodiment, when true PPS is available, it can be used to estimate multipath bias and accurate true distance. The receiver estimates the distance using a sample of the signal, eg, from the ADC. The receiver of one embodiment uses a high speed clock to determine the time difference between the occurrence of the PPS and the first edge of the sample ADC clock. This allows the distance estimated by the receiver based on the ADC samples to be corrected for the difference between when the true PPS occurs and when the ADC samples the data, and therefore the ADC samples Enables estimation of the true distance of the receiver to better accuracy than the clock resolution. In the context of the discussion in the above paragraph, PPS refers to a pulse whose edges are aligned to a standard timing base such as GPS pulse per second (PPS) timing or have a known offset thereto.

  In another embodiment, a wide area differential positioning system can be used to correct timing errors from the tower. FIG. 9 is a block diagram of a differential WAPS system, under an embodiment. A reference receiver (located at a pre-studied location) is used to receive signals from all nearby towers. Although the differential GPS principle is applied to this method, dealing with the effects of non-line-of-sight on the ground makes it unique. The reference receiver pseudorange (code phase) measurements per tower are time-tagged and then sent to the server. The phase-based distance of the received code measured at the reference receiver for towers j and i can be written as:

here,

Is a reference receiver for transmitting the geometric distance of tower j, where dt _ref and dt ^j are reference receiver clock offsets referenced to respective antennas with respect to a common reference time (eg, GPS time), respectively. And the transmitter clock offset, c is the speed of light,

Is the measurement noise.

The clock timing difference between towers i and j, dt ⁱ -dt ^j, is calculated at the server by subtracting the above two equations and using the known geometric distance from the reference receiver to the transmission tower Is done. This allows removal of timing differences between transmitters in rover / mobile station measurements. That averaging over time can be used to obtain a better (eg, less noisy) estimate of the time difference dt ⁱ -dt ^j when the clock used in the transmit tower is relatively stable. Please keep in mind.

  The rover / mobile station pseudorange measurements are also time-tagged and sent to the server. The phase-based distance of the received code measured at the rover / mobile station can be written as:

By subtracting and rearranging the above two equations, the result is

become.

and

Note that is the measured quantity and the quantity dt ⁱ −dt ^j is calculated from the reference receiver measurements.

and

Can be written in terms of the unknown coordinates of the receiver and the known coordinates of the transmission towers i and j. Using three distance measurements, the two distance difference equations can be formed as above to get a two-dimensional position solution, or using four distance measurements, the three distance difference The equation can be formed as above to obtain a three-dimensional position. Using the least squares solution with additional measurements, the amount of noise

and

Can be minimized.

  Alternatively, the timing difference correction can be sent back to the mobile station to correct the error in situ and to facilitate position calculation at the mobile station. Difference correction can be applied to many of the same transmitters that can be seen by both the reference station and the mobile station. This method can conceptually allow the system to operate without tower synchronization, or, in the alternative, allow any residual clock error to be corrected in a roughly synchronized system. can do.

  Another approach is a stand-alone timing approach as opposed to the differential approach above. One form of establishing timing synchronization is by having the GPS timing receiver receive a DGPS correction value from a DGPS reference receiver in the same area at each transmission tower in a particular area. A DGPS reference receiver installed at a known location considers its own clock as the reference clock and finds a correction value for the pseudorange measurement to the GPS satellite it tracks. DGPS correction values for a particular GPS satellite typically include satellite position and clock errors and total error due to ionospheric and tropospheric delays. Since the line of sight between the DGPS reference receiver and the GPS satellite does not change significantly in the direction within this neighborhood, this total error is near the DGPS reference receiver (usually about 100 km with the DGPS receiver at the center). Will be the same for any pseudorange measurements made by other GPS receivers. Thus, a GPS receiver that uses the DGPS correction value transmitted by the DGPS reference receiver for a particular GPS satellite uses the correction value to remove this total error from that pseudorange measurement for that satellite. However, in the process, the GPS receiver adds the DGPS reference receiver clock bias with respect to GPS time to the pseudorange measurement. However, since this clock bias is common for all DGPS pseudorange corrections, its effect on the timing solutions of different GPS receivers is a common bias. However, this common bias does not give a relative timing error at different GPS receiver timings. Specifically, if these GPS receivers are timing GPS receivers (at known locations), all of those GPS receivers are synchronized to the DGPS reference receiver clock. When these GPS timing receivers drive different transmitters, their transmissions are also synchronized.

  Instead of using correction values from DGPS reference receivers, similar correction values transmitted by Wide Area Augmentation System (WAAS) satellites are used by GPS timing receivers and transmitters they drive. Can be synchronized. The benefit of WAAS is that the reference time is not the reference time of the DGPS reference system, but the GPS time itself maintained by an accurate set of atomic clocks.

  Another approach to achieving precise time synchronization between towers over a wide area is to use time transfer techniques to establish timing between tower pairs. One technique that can be applied is referred to as “common view time transfer”. FIG. 10 illustrates common view time transfer, under an embodiment. A GPS receiver in the transmitter with a common satellite view is used for this purpose. The code phase and / or carrier phase measurements from each of the towers for satellites in the common view are time-tagged periodically (eg, at least once per second) by the GPS receiver, and these measurements are analyzed. Sent to the server.

  GPS code observable

(The signal emitted by satellite “i” and observed by receiver “p”) can be written as:

here,

Is

Receiver-satellite geometric distance equal to

Is the receiver antenna position at the time of signal reception,

Represents the satellite position at the time of signal emission,

and

Are the ionospheric delay and tropospheric delay, respectively,

and

Are the receiver hardware group delay and the satellite hardware group delay. variable

Includes the effects of the antenna, the cable connecting it to the receiver, and the delay within the receiver itself. Furthermore, dt _p and dt ⁱ are the receiver clock offset and satellite clock offset with respect to GPS time, respectively, c is the speed of light, and ε _R is the measurement noise.

  The common view time transfer method is a single differential code observable

And this is

As the difference between code observables measured simultaneously by two receivers (referred to as “p” and “q”). In calculating a single differential observable, the group delay time in the satellite as well as the satellite clock error is negated. Note also that in the above equation, the tropospheric and ionospheric perturbations cancel (or may be modeled, for example, when the receiver separation is large). After the group delay difference between the receivers has been calibrated, the desired time difference c (dt _p −dt _q ) between the receiver clocks can be found from this equation. A single difference across multiple time and satellite measurements can be combined to further improve the quality of the estimated time difference.

  In a similar manner, a single differential carrier phase equation for common view time transfer can be written as:

Note that since the initial phase ambiguity and integer ambiguity exist in the above equation, the time transfer cannot be determined directly using a single phase difference. The combined use of code and phase observations makes it possible to utilize absolute information about the time difference from the code and accurate information about the occurrence of the time difference from the carrier phase. Error variance with a single difference in carrier phase is significantly better than a single difference in code phase that leads to better time transfer tracking.

  The per-to-tower result error for a given satellite is sent back to the tower for correction, applied at the tower, and sent to the receiver over the communication link for additional correction to be performed by the receiver. Or sent as a broadcast message along with other timing correction values from the tower. In certain examples, measurements from towers and receivers may be post-processed on the server for better location accuracy. Single-view GPS timing receiver or multi-channel timing receiver that makes C / A code measurements and / or carrier phase measurements from other satellite systems such as L1 and / or L2 or Galileo / Glonass, common view time transfer Can be used for this purpose. In a multi-channel system, information from multiple satellites in a common view is captured at the same moment by a receiver.

  An alternative mechanism for “common view time transfer” is that different timing GPS receivers in the local area (each fed to a corresponding transmitter) only derive a common satellite in its timing pulse derivation (eg 1 pulse per second). To ensure that no attempt is made to correct timing pulses to be aligned to GPS (or UTC) seconds. The use of the common view satellite means that common errors in the timing pulse (such as common GPS satellite position error, common GPS satellite clock error, ionosphere delay compensation error, and troposphere delay compensation error) are almost the same magnitude. The relative error in the timing pulse is reduced. Since only relative timing errors are a problem in positioning, there is no need for server-based timing error correction. However, the server can give commands to different GPS receivers as to which GPS satellite to use in deriving timing pulses.

An alternative to time transfer is the “bidirectional time transfer” technique. FIG. 11 illustrates bidirectional time transfer under an embodiment. Consider two towers used to time each other. Transmission from each of the two transmitters begins with a PPS pulse, and a time interval counter is started on the receiving section (WAPS receiver) of the transmitting tower. The received signal is used to stop the time interval counter on both sides. The results from the time interval counter are transmitted over the data modem link to the WAPS server, where these results are compared with the transmission time and the timing error between the two towers can be calculated. This can be extended to any number of towers. In this way, the relationship between [Delta] T _j of the counter measurements [Delta] T _i and tower j at tower i, and i and the time difference dt _ij between the clocks at j,

Where can be represented as

and

Is the tower transmitter delay and

and

Is the tower receiver delay. After the transmitter and receiver delays are calibrated, the time difference can be estimated.

  In addition to time transfer between towers, the tower timing relative to GPS time can be found by a GPS timing receiver used for common view time transfer.

After accounting for receiver delay, satellite clock error, and ionosphere / troposphere error, using distance measurements as, a local clock time correction relative to GPS time dt _p is calculated. The receiver delay δ _{R, p} can be calibrated by group delay measurements. Information from the GPS satellite navigation message (obtained either via demodulation or from a server), dt ⁱ and

Can be used to calculate satellite timing corrections that eliminate the effects of. Similarly, tropospheric and ionospheric delay effects are minimized using corrections from external models. The ionospheric correction can be obtained, for example, from a WAAS message. Alternatively, a combination of clock and ionosphere / troposphere correction can be derived from RTCM DGPS corrections for pseudoranges when available.

  The offset to GPS time can also be transmitted from the tower as part of the data stream. This allows any WAPS receiver that acquires a WAPS signal to provide accurate GPS time and frequency aids to significantly reduce GNSS search requirements within the GNSS receiver.

  In system embodiments, the broadcast transmitter can be used only to provide localized indoor location determination. For example, in a fire safety application, a WAPS transmitter is located at more than two broadcast stations (eg, can be fire engines). The towers synchronize with each other by one of the many means and broadcast signals previously mentioned. Bandwidth and chipping rate are scaled based on the spectral availability and accuracy requirements in that region for that application at that time. The receiver is informed about system parameters via a communication link to the device.

  FIG. 12 is a block diagram of a receiver unit, under an embodiment. The beacon signal is received by the antenna on the receiver unit, down-converted, demodulated, decrypted and supplied to the positioning engine. The receiver provides all the information to accurately reconstruct the signal. The receive antenna can be an omni-directional antenna, or in the alternative can be multiple antennas / arrays, etc. that provide diversity. In another embodiment, mixing and downconversion can be performed in the digital domain. Each receiver unit includes or uses a unique hardware identification number and a computer generated private key. In general, each receiver unit stores the last few locations in non-volatile memory and can be remotely queried later for the last few stored locations. Based on the availability of spectrum within a given area, the transmitter and receiver can adapt to the available bandwidth and change the chipping rate and filter bandwidth for better accuracy and multipath resolution. Can do.

  In one embodiment, digital baseband processing of the received signal is achieved using a commercially available GPS receiver by multiplexing / supplying signals from a GPS RF section with a WAPS RF module. FIG. 13 is a block diagram of a receiver with a WAPS RF module, under an embodiment. In some examples, the RF module includes one or more of a low noise amplifier (LNA), a filter, a down converter, and an analog-to-digital converter. In addition to these components, the signal can be further conditioned to meet GPS receiver input requirements using additional processing on a chip, custom ASIC, FPGA, DSP, or microprocessor. Can be attached. Signal conditioning includes digital filtering for in-band or out-of-band noise (such as ACI-adjacent channel interference), conversion of intermediate or baseband frequency from the WAPS receiver frequency to the GPS IC, and the GPS IC converts the WAPS signal Digital signal strength adjustments to allow processing, automatic gain control (AGC) algorithms to control the WAPS front end, etc. can be included. Specifically, frequency conversion is a very useful feature as it allows the WAPS RF module to work with any commercially available GPS receiver. In another embodiment, the entire RF front end chain, including signal conditioning circuitry for the WAPS system, can be integrated onto an existing GPS die that includes the GPS RF chain.

  In another embodiment, when access to the digital baseband input is not available, the signal can be up-converted / down-converted from any band to the GPS band and fed to the RF section of the GPS receiver can do. FIG. 14 illustrates signal up-conversion and / or signal down-conversion, under an embodiment.

  In another embodiment, a plurality of RF chains or tunable RF chains can be used with a transmitter of a WAPS system to use the most effective frequency of operation in a given area, whether wide-area or local. Can be added to both receivers. The selection of the frequency can be determined by spectral cleanliness, propagation requirements, and the like.

  Similarly, WAPS can temporarily use a receive chain in a receiver system that includes multiple receive chains. For example, a wideband CDMA (W-CDMA) receiver system includes two receive chains to improve receive diversity. Thus, when WAPS is used in a W-CDMA receiver system, one of the two native receive chains of W-CDMA can be temporarily used for receiving and processing the WAPS signal. FIG. 15 is a block diagram of a receiver system having multiple receive chains that can be temporarily used to receive and process a WAPS signal in one of the receive chains, under an embodiment. In this example, the diversity receive chain can be used to temporarily receive and process the WAPS signal. Alternatively, a GPS receive chain can be used to temporarily receive and process the WAPS signal.

  The wireless front end can be shared between the WAPS and another application. Some parts of the front end can be shared and some parts may be used on a mutually exclusive basis. For example, if the die / system already has a TV (NTSC, ATSC, or DVB-H, MediaFLO, etc.) tuner front end that includes an antenna, the TV tuner radio and antenna can be shared with the WAPS system. . They can operate on a mutually exclusive basis in that the system either receives a TV signal or a WAPS signal at a given time. In another embodiment, if it makes it easier to add a WAPS RF section to such a system, the antenna is shared between the TV tuner and the WAPS system so that both systems operate simultaneously. Can be made possible. If the system / die has a radio such as an FM radio, the RF front end can be modified to handle both the WAPS system and the FM radio, and these radios are mutually exclusive Can work on any basic. Similar changes can be made for systems with several RF front ends operating at close frequencies close to the WAPS RF band.

  WAPS reception for clock sources such as crystal, crystal oscillator (XO), voltage controlled temperature compensated crystal oscillator (VCTCXO), digitally controlled crystal oscillator (DCXO), temperature compensated crystal oscillator (TCXO) used in GNSS subsystem Can be shared with the WAPS receiver to provide a reference clock to the receiver. This sharing can be done on the die or off-chip. Alternatively, the TCXO / VCTCXO used by any other system on the cellular phone can be shared with the WAPS system. FIG. 16 is a block diagram illustrating clock sharing in a positioning system, under an embodiment. Note that a transceiver or processor system block may refer to various systems. The transceiver system that shares a clock with the WAPS system can be a modem transceiver (eg, a cellular modem, a WLAN modem, or a BT modem) or a receiver (eg, a GNSS receiver, FM receiver, or DTV receiver). These transceiver systems can optionally control the VCTCXO or DCXO for frequency control. Note that the transceiver system and the WAPS system can be integrated into a single die, or can be separate dies and do not affect clock sharing. The processor can be any CPU system (ARM subsystem, digital signal processor system, etc.) that uses a clock source. In general, when VCTCXO / DCXO is shared, the frequency correction applied by other systems may be slowed down as much as possible to facilitate WAPS operation. Specifically, frequency updates within the maximum integration time used in the WAPS receiver may be limited to allow better performance of the WAPS receiver (ie, minimize SNR loss). Information regarding the state of the WAPS receiver (especially the level of integration used, the acquisition versus tracking state of the WAPS system) may be exchanged with other systems for better adjustment of the frequency update. it can. For example, frequency updates can be paused during the WAPS acquisition phase, or frequency updates can be scheduled when the WAPS receiver is in a sleep state. The communication can be in the form of control signals or alternatively in the form of messages exchanged between the transceiver system and the WAPS system.

  WAPS broadcasts signals and messages from the tower in a manner that does not require modification of the baseband hardware of conventional GPS receivers to support both WAPS and traditional GPS systems. The importance of this is that the WAPS system has only half of the usable bandwidth of the GPS C / A code system (which affects the chip rate), but the WAPS broadcast signal is a commercial grade C / A code GPS receiver. Lies in the fact that it is configured to operate within limits. Furthermore, based on signal availability, the algorithm determines whether the GPS signal must be used to determine position, or whether the WAPS signal or a combination thereof should be used to obtain the most accurate location. to decide.

  Data transmitted over the Gold code on the WAPS system can be used to transmit GNSS assistance information in the case of a hybrid GNSS-WAPS usage scenario. Assistance can be in the form of SV trajectory parameters (eg, ephemeris and calendar). Assistance can also be specialized for SVs that are visible in the local area.

  Furthermore, timing information obtained from the WAPS system can be used as delicate time aids for the GNSS system. Since the WAPS system timing is aligned to GPS (or GNSS) time, matching the sign and bits of the WAPS signal and reading the data stream from any tower provides a rough knowledge of GNSS time. In addition, position resolution (receiver clock bias is a by-product of position resolution) accurately determines the WAPS system time. After the WAPS system time is known, delicate time aids can be provided to the GNSS receiver. Timing information can be transferred using a single hardware signal pulse whose edges are tied to the internal time base of the WAPS. Note that the WAPS system time maps directly to GPS time (more generally, along with the GNSS time since the time base of the GNSS system is directly related). The GNSS must be able to latch its internal GNSS timebase count upon receipt of this edge. Alternatively, the GNSS system must be able to generate pulses whose edges are aligned to the internal time base, and the WAPS system must be able to latch its internal WAPS time base. The WAPS receiver then sends a message with this information to the GNSS receiver, allowing the GNSS receiver to map its time base to the WAPS time base.

  Similarly, a local clock frequency estimate can be used to provide frequency aiding to the GNSS receiver. Note that the frequency estimates from the WAPS receiver can be used to refine the frequency estimates of the GNSS receiver, regardless of whether they share a common clock. When the two receivers have separate clocks, an additional calibration hardware block or software block is required to measure the clock frequency of one system relative to the other system. Hardware blocks or software blocks may be provided in the WAPS receiver section or in the GNSS receiver section. The frequency estimate from the WAPS receiver can then be used to refine the frequency estimate of the GNSS receiver.

  Information that can be transmitted from the WAPS system to the GNSS system may also include an estimate of the location. Location estimates can be more accurate based on approximations (eg, determined by the PN code of the WAPS tower) or actual location estimates in the WAPS system. In order to provide a more accurate estimate of the position that can be used from the WAPS system to better support the GNSS system, another estimate of the position (e.g., cellular) Note that this can be combined with a coarse position estimate from ID-based positioning. FIG. 17 is a block diagram of assistance transfer from a WAPS receiver to a GNSS receiver, under an embodiment.

  The GNSS receiver improves the performance of the WAPS receiver in terms of Time-To-First-Fix (TTFF), sensitivity, and location quality by providing location, frequency, and GNSS time estimates to the WAPS receiver. Can also help. As an example, FIG. 18 is a block diagram illustrating the transfer of aiding information from a GNSS receiver to a WAPS receiver, under an embodiment. Note that the GNSS system can also be replaced by LORAN, e-LORAN, or similar ground positioning systems. The location estimate can be either partial (eg, altitude or 2D position), complete (eg, 3D position), or raw distance / pseudorange data). Distance / pseudo-range data must be provided along with the location of the SV (or a means for calculating the location of the SV, such as SV trajectory parameters) to allow the use of this distance information in a hybrid solution. Don't be. All location aid information must be provided with a metric indicating its quality. When providing GNSS time information (which can be transferred to the WAPS system using hardware signals), the offset of the GNSS time relative to GPS time (if present) allows use at the WAPS receiver. Must be provided to. The frequency estimate can be provided as an estimate of the clock frequency along with a confidence metric (which indicates the estimated quality of the estimate, eg, the maximum expected error of the estimate). This is sufficient when the GNSS system and the WAPS system share the same clock source. When the GNSS system and the WAPS system use separate clocks, the GNSS clock is also used to calibrate (ie, estimate the relative clock bias of the WAPS with respect to the GNSS clock). Or in the alternative, the WAPS system must provide its clock to the GNSS system, and the GNSS system uses the calibration estimate (ie, the WAPS relative clock relative to the GNSS clock). An estimate of the bias) must be provided.

  To further improve the sensitivity and TTFF of the WAPS receiver, assistance information (such as what is otherwise decoded from information transmitted by the tower) can be transferred by other communication media (cellular telephone, WiFi, SMS, etc.) It can be provided from the WAPS server to the WAPS receiver. If there is already "calendar" information available, the WAPS receiver job is simplified because the receiver only needs to be time aligned to the transmitted waveform (no bit alignment or decoding is required). Eliminating the need to decode the data bits reduces TTFF and thus saves power because the receiver does not need to be turned on continuously to decode all bits. FIG. 19 is a configuration of an example in which WAPS assistance information is provided from a WAPS server, under an embodiment.

A beacon can be added to the receiver to further improve local positioning. The beacon can include a low power RF transmitter that periodically transmits a waveform having a signature based on the device ID. For example, the signature can be a code that uniquely identifies the transmitter. Associated receivers either through discovery of signal energy peaks when scanning in all directions, or through direction discovery (using signals from multiple antenna elements to determine the direction of signal arrival) The transmitter location can be found with relatively higher accuracy.
Multipath signal resolution Multipath resolution is critical in positioning systems. Wireless channels are often characterized by a set of randomly changing multipath components with random phases and amplitudes. To make positioning accurate, the receiver algorithm, if present, has a line of sight (LOS) path (becomes the first arrival path) or the first arrival path (which may not necessarily be a LOS component) It is important to solve the problem.

  Traditional methods often operate as follows. (1) The received signal is cross-correlated with the transmitted pseudo-random sequence (eg, a Gold code sequence known at the receiver), and (2) the receiver locates the first peak of the resulting cross-correlation function. Estimate that the timing of the first arriving path is the same as the timing indicated by this peak position. As long as the minimum multipath separation is much greater (and often not) the reciprocal of the available bandwidth, these methods work effectively. Bandwidth is a valuable necessity and a method that can resolve multipath with a minimum amount of bandwidth is highly desirable to improve system efficiency.

  Depending on the channel environment (including multipath and signal strength), an appropriate method is used to obtain an estimate of the earliest arriving path. For best resolution, high-resolution methods are used, but for moderate performance at low SNR, the cross-correlation peak sample and some characteristics of the correlation function around the peak are directly The more traditional method used is applied.

Consider a quantized received signal y [n] sampled at a rate f _s given by:

Where y [n] is the effective channel

Is a received signal that is a convolution of the transmitted pseudo-random sequence x [n], h _tx [n] is a transmit filter, h _rx [n] is a receive filter, and h [n] is It is a multipath channel.

  One way to find the peak position is by peak interpolation using values that surround the obvious peak position. Interpolation can be a quadratic equation that uses one value on either side of the peak, can use a higher order polynomial that uses two or more samples near the peak, or relates to the actual pulse shape The best fit can be used. In the case of quadratic interpolation, the quadratic equation is applied to the peak value and the value directly surrounding the peak. The peak of the quadratic equation determines the peak position used for ranging. This method is fairly robust and can work well with low SNR.

Alternative embodiments may use values other than the peak position as the reference position. Note that the DLL actually uses the peak position as the reference position on the correlation function, but this method uses a different point from the peak as the reference. This method is motivated by the fact that the leading edge of the correlation peak is less affected by multipath than the falling edge. For example, a point of 75% of the chip _Tc from the peak on the correlation function that is not distorted (no channel effect) can be used as the reference point. In this case, the portion of the interpolated z [n] function that matches this 75% point is selected and the peak is found as a point 25% away from this point Tc. Another alternative peak correlation function-based method can use peak shape (measurement of peak distortion, eg, peak width). Starting from the peak location, based on the shape of the peak, a correction for the peak location is determined to estimate the first arriving path.

  High resolution methods are a class of efficient multipath solutions that use eigenspace decomposition to locate multipath components. Methods such as MUSIC and ESPIRI fall under this class of solution. They are a very powerful scheme in that they can effectively resolve much closer spaced multipath components for the same given bandwidth than traditional methods. The high resolution earliest arrival time method attempts to estimate the arrival time of the earliest path directly rather than inferring the peak position from the peak value. In the following, it is assumed that a coarse acquisition of the transmitted signal is already available at the receiver and that the start of the pseudo-random sequence is roughly known at the receiver.

  FIG. 20 is a flow diagram for estimating the earliest arriving path in h [n], under an embodiment. The method for determining the earliest path includes, but is not limited to, the following operations.

  1. The received sample y [n] is cross-correlated with the transmission sequence x [n] to obtain the result z [n]. Cross-correlation is about convolution

When this is written,

Can be rewritten as: Here, φ _xx [n] is an autocorrelation function of a pseudo-random sequence.

2. Locate the first peak of z [n] and denote it as n _peak . Extract wL samples to the left of the peak of z [n] and wR samples to the right of the peak, and denote this vector as pV.

pV = [z [n _peak −wL + 1]... z [n _peak + wR]]
The vector pV represents a useful part of the cross-correlation result z [n]. In the ideal case, no channel distortion, when the channel BW is not limited, selecting wL = wR = f _s T _c is sufficient to determine the timing of the received signal. In the presence of restricted BW, for the case where the pseudo-random code x [n] is a sequence of + l / −l, the optimal method for selecting wL and wR is respectively

Is to select them as non-zero values (or more generally, values greater than a certain threshold, defined as a fraction of the peak value) present on the left and right sides of the peak . One other consideration in selecting wL and wR is to select uncorrelated noise samples that are sufficient to obtain sufficient information about the noise subspace. In addition, integer wL and wR must be selected to include all possible multipath components, particularly on the left side (ie via wL selection), to help resolve common sense multipath components. I must. Including too many samples above f _s T _c increases the amount of noise introduced into the pV vector and therefore must be reduced. Through simulation and experiment, the usual set of values for wL and wR are 3f _s T _c and 3f _s T _c , respectively.

z [n] (and then pV) includes the effects of the autocorrelation function of channel h [n], transmit filter h _tx [n], receive filter h _rx [n], and pseudo-random sequence φ _xx [n] Please note that. Other effects need to be removed to estimate the earliest arriving path in the channel. In many cases, the transmit pulse shape and the receive pulse shape are matched for the best noise performance, but that constraint is not required for this algorithm to work. The reference correlation function is

Which needs to be estimated and removed before pV can be used to estimate the earliest arriving path.

3. The reference correlation function φ _ref [n] is then estimated. One way to obtain the reference cross-correlation is as follows. Steps 1-2 are performed on the ideal channel (so-called “cabled link”) to obtain the corresponding peak vector pV _Ref . pV _Ref contains useful samples of the reference correlation function φ _ref [n]. FIG. 21 is a flow diagram for estimating a reference correlation function, under an embodiment.

  The “cabled link” method bypasses the receiver front end (eg, the antenna) from the transmitter front end (where the power amplifier and transmit antenna is bypassed) through the “ideal” channel (eg, cable). ) To transmit the modulated signal. Note that an “ideal” channel can have some delay and attenuation, but should not add any other distortion and have a high SNR. For best performance, “cabled” criteria need to be generated separately for each pseudo-random sequence, since pseudo-random sequences have different autocorrelation functions and thus different criteria. Since the autocorrelation sidelobe can be misinterpreted for multipath unless it is sufficiently attenuated, the best autocorrelation function (specifically, the autocorrelation sidelobe yields the best overall performance of the time-resolved method). It is also critical to correctly select the PRN with respect to their termination of (which must be well suppressed compared to the peak).

  Assuming that the transmit filter response is controlled, one calibration of the response on the cabled link is required for each receiver during production. If the receiver filter characteristics can be controlled (eg, for a bundle of receivers), the calibration on the cabled link for response is further reduced to one calibration measurement for the set of receivers. be able to.

An alternative way of determining the reference correlation function φ _ref [n] is to analytically calculate the individual components φ _xx [n], h _tx [n], and h _rx [n] and to calculate the reference correlation function φ _ref [ n] to convolve them to reach n]. It should be noted that this method depends on the degree to which the transmit filter impulse response and the receive filter impulse response can be controlled in an actual implementation.

  4). Improve the SNR of the pV estimate by coherently averaging across multiple Gold codes and even across multiple bits. Averaging over multiple bits can be performed coherently after a determination is made that individual bits are transmitted. In other words, decision feedback is used before integration over bits. Note that an improved SNR can be obtained equally by performing averaging with the cross-correlation function estimation in step 1.

5. Vector _{pV Freq} and _{pV Ref} length _{N fft, Freq} In order to obtain _{respectively, N fft - (wL + wR} ) Fast Fourier transform of length _{N fft} of pV and _{pV Ref} with zero padding zeros (FFT) Calculate The optimal value of N _fft is obtained by checking multipath resolution through simulation using both the synthesized channel and the actually measured channel. A typical value for N _fft was found to be 4096 or higher.

pV _Freq = FFT [pV zero padding]
pV _{Ref, Freq} = FFT [pV _Ref zero padding]
6). To obtain a frequency domain estimate of channel h [n] (destroyed by noise)

Calculate If the received sequence y [n] is N _os (ie, for a transmit pulse shape band limited to +/− 1 / Tc,

), And the transmit and receive pulse shaping filters are exactly band-limited at BW = 1 / Tc, precisely to around H _full [k] DC

The positive and negative samples are non-zero (ie usable) with respect to the actual channel estimate H _real [k]. From our research, we found that both sides of the DC

Samples must be chosen for the best performance of the solution algorithm and α> 1 is selected based on the actual pulse shaping filter and autocorrelation function φ _xx [n] used in the transmitter and receiver It was concluded that Note that including the frequency transition band of φ _ref [n] causes noise enhancement, and α is chosen to be large enough to eliminate these frequencies in the selected samples. However, selecting too large α causes loss of signal information. A preferred choice of α = 1.25 for an actual band-limited function based on a raised cosine filter shape with a small extra bandwidth was used in the implementation.

7). When the DC component of H _full [k] is at index 0, the reduced H vector, H [] is
H = [H _full [N _fft −N + 1]... H _full [N _fft ] H _full [0] H _full [1]... H _full [N]]
Is defined.

  8). A matrix P is constructed from the reduced channel estimation vector H [k].

Here, 1 <M <2N is a parameter, and () ′ represents a conjugate of a complex number.

The estimated covariance matrix R of the reduced channel estimation vector H [k] is R = P × P ′
It is defined as

  If M is chosen to be too small (close to 1), the eigenvalues of R are very limited in number, so that high resolution algorithms can draw between signal and noise. Disappear. If M is chosen to be too large (close to 2N), the covariance matrix estimate R is unreliable because the amount of averaging in obtaining the covariance is inadequate. The variance matrix R is also a rank drop. Therefore, a value of M that is exactly in the middle of its acceptable range, ie M = N, is a good choice. This was also confirmed empirically.

9. R = UDV '
Singular value decomposition (SVD) on R. Here, U is a matrix of left singular vectors, V is a matrix of right singular vectors, and D is a diagonal matrix of singular values.

10. sV = Construct a sorted vector of singular values sV as diagonal elements of D sorted in descending order.

11. The next important step is to separate the signal and noise subspaces. In other words, the index ns in the vector sV is selected so that the singular values sV [ns + 1]... SV [N] correspond to noise. A vector of noise singular values is defined as sV _noise .

  There are a number of ways in which the singular values corresponding to the noise subspace can be separated and a representation of the base vector of the noise subspace can be found.

a) T1 which is a function T ₁ = f (SNR) of the signal-to-noise ratio (eg, SNR on chip) is a threshold value;

All smaller singular values.

  FIG. 22 is a flow diagram for noise subspace estimation, under an embodiment.

  b) min

All singular values less than. Where L is a selectable parameter greater than the delay spread (eg, N / 2) and T ₂ is another threshold determined empirically (normal value is 1000) Can).

  FIG. 23 is a flow diagram for noise subspace estimation under an alternative embodiment.

  c) Another method involves determining the noise subspace by repeatedly estimating the SNR for different partitions of the noise subspace and the signal plus noise subspace and comparing it with another estimate of the SNR. FIG. 24 is a flow diagram for noise subspace estimation under another alternative embodiment.

    1) Calculate the SNR estimate as follows:

i. Assume that the noise is represented by sV () n _s , n _s +1,. Noise covariance

Calculate as

      ii. Signal power

Calculate as

      iii. Estimated SNR

2) An alternative estimate of SNR is obtained via other methods (eg, SNR on chip). One way to directly estimate the SNR is as follows:
i. If the received data samples (after resampling to removal and sample and reference numeral decorrelation spaced the Tc of the frequency error) is given by X _i (where, X _i is interpolated peak position The chip interval is opened starting from

X _i = S + N _i
ii. Signal is

Is estimated as

      iii. Noise

Is estimated as

      iv. SNR is

Is estimated as

    3) The following conditions

Is selected as sV (ns, ns + 1,..., M).

  d) Another method uses c) 1) to iteratively estimate the SNR for different partitions of the noise and signal subspaces;

Determining the noise subspace by selecting the partition n _start to be

  FIG. 25 is a flow diagram for noise subspace estimation under another alternative embodiment.

  e) FIG. 26 is a flow diagram for noise subspace estimation under another alternative embodiment.

    1)

Define The first wLen singular values then represent the significant signal plus the singular value of the noise subspace or noise subspace (the remainder of the singular value represents the correlated noise and signal and the quantization effect).

    2) Calculate the SNR estimate as follows:

i. Assuming that the noise is represented by sV (i): i = n _s , n _s +1 ... wLen; l <n _s ≦ wLen,

Calculate the noise variance as

      ii.

Calculate the signal power as

      iii. Estimated SNR

3) Define n _start = [minimum n _s : SNR _est (n _s )> (SNR _est (wLen) −thresDB)]. n _start up to winLen represents a noise singular value. A typical value for thresDB is 10.

12 Select the right singular vector of the corresponding noise to construct V _N , that is, select all vectors in V corresponding to the noise singular value and construct the noise subspace matrix V _N.

  13. Estimate the arrival time of the first path.

    a)

It is defined as

b) For the range of values of τ (τ∈ [τ _max , −τ _max ]),

Calculate The search resolution Δτ can be selected as small as required. As an example, τ _max = 5 and Δτ = 0.05 so that τ is searched in the range [−5, 5] in steps of 0.05.

14 The peak of Ω (τ) provides the position of the channel impulse relative to the coarse peak n _peak . Theoretically, the first peak corresponds to the LOS path. It is possible to control τ _max based on information about the propagation environment that can be encoded in the transmission from the base station. For example, when delay spread is large, τ _max can be selected to be larger (eg, 10), and when delay spread is smaller, τ _{max is set} to a smaller value (eg, 4). You can choose.
Combination Methods Apart from the stand-alone methods described above, many other combination methods are possible. A combination of schemes based on SNR on chip is an effective method. Next, a list of combination methods that can be actually realized will be described.

  1. For a chipSNR that is less than chipSNRRef, select method 12 (d) to select a noise singular value. Otherwise, select method 12 (a).

  2. For chipSNR greater than chipSNRRef, select a noise singular value and select method 12 (d) to estimate the peak position. Otherwise, start with the cross-correlation function z [n] and use direct peak estimation techniques (peak interpolation, peak shape, etc.).

  3. For chipSNR smaller than chipSNRRef, select method 12 (e) to select a noise singular value. Otherwise, select method 12 (a).

A typical value for chipSNRRef is 10 dB.
Position calculation The location of the receiver unit is determined by a positioning engine available in either the terminal unit or the server. The receiver can use distance measurements from the system, or combine any measurements from other occasional signals with system distance measurements. If the measurements are derived from known locations, a sufficient set of distance measurements will result in position determination. The equation for the distance in 3D space is

Given by.

The transmitter location is given by (x _i , y _i , z _i ) and the unknown location of the mobile unit is given by (X, Y, Z) in a local coordinate frame. Three or more transmitters make three or more distance measurements that are used to calculate a fixed point. Since the receiver time is not synchronized with the WAPS timing, the measurement also has an additional item of receiver time bias.

R _i = r _i + cΔt
This formula is later referred to as a “pseudo distance measurement formula”. Note that the time bias is common because the transmitters are timing synchronized. The pseudorange must be corrected in order to correct the available transmission timing from the data stream embedded in the transmission from each transmitter. This delta time bias creates a new unknown parameter, so at least four measurements are used in the solution. For barometric altimeter measurement, information necessary for the solution is Baro = (Z _b −Z)
As offered.

  One way to solve these nonlinear simultaneous equations is to linearize the problem at an arbitrary initial point and then iteratively find a correction for this initial position so that it repeatedly leads to the final solution.

  This method uses an initial guess for the X, Y, Z solution, so the centroid of the transmitter is

Used as. The final position solution is
(X, Y, Z, Δt) = (X ₀ , Y ₀ , Z ₀ , Δt ₀ = 0) + (dX, dY, dZ, dΔt)
Is assumed to be of the form The geometric distance can be expanded with a Taylor series with respect to (X, Y, Z, Δt) = (X ₀ , Y ₀ , Z ₀ , Δt ₀ ).

Here, the estimated distance is

And the partial derivative is
∂R / ∂x = ∂r / ∂x = (x _i −X) / r _i ∂R / ∂Δt = c
_{∂R / ∂y = ∂r / ∂y =} (y i -Y) / r i
_{∂R / ∂z = ∂r / ∂z =} (z i -Z) / r i
Given by.

  In this embodiment, four linear equations with four unknowns are shown. The additional distance estimate makes more rows in the matrix. The result is a set of expressions

It is. The last row of the observation matrix represents barometric altimeter measurements. The three one columns represent the same time bias for all three distances. These equations have the form Ax = b. The solution is x = A ⁻¹ * b. Note that in the absence of barometer measurements, another additional measurement adds an additional row similar to rows 1 through 3 of the above matrix. This additional measurement allows estimation of the receiver altitude. When there are more available measurements than the number of unknowns, the solution is based on a pseudo inverse matrix of A given by A ₊ = (A ^T A) ⁻¹ A ^T , and the least squares solution is x = A ₊ Note that ⁻¹ b. When the quality of measurement is not equal, the best way to solve the equation Ax = b in the least square sense is to use a weight proportional to the SNR for the error from each equation. This _leads to ^{A + = (A T WA)} -1 A T W at which the solution _{x =} ^{A + -1} b. The diagonal weighting matrix W is formed by weights proportional to the noise variance of the measured values. The solution of these equations is

Make delta correction values for X, Y, Z, and delta time estimates so that

  This completes the first iteration of the method. The updated position and time bias estimate replaces the initial guess, and the algorithm continues until the delta parameter is below a certain threshold. A normal stopping point is for a norm of delta values below a certain threshold (eg 1 meter).

  The simultaneous linear equations in GPS are solved using least squares and initial guesses about the user's location so that the algorithm converges to the final user location. Linearization is based on the basic assumption that the distance between the satellite and the user position is greater than the distance between the ground user position and the estimated position. In order for the same set of equations to work in the terrestrial environment (which has a small shape), the initial guess should be based on the center of gravity (described above), the point close to the transmitter where the received signal is strongest Or can be obtained by a direct method that gives a closed form solution by a sequence of equations without iteration. When the initial guess is near the centroid or the transmitter with the strongest received signal, the initial guess is improved using the least squares method. When the initial guess is obtained by a straightforward method that gives a closed form solution with a sequence of equations without iterations, the initial solution itself is the final solution, which is the measured value (such as signal strength and elevation angle). The least squares method is used only when there are more measurements (and therefore equations) than unknowns, along with the weighted individual measurements, by using the expected error of Improved. Furthermore, if the sequence of measurements has to be processed in time, the solution obtained above can be fed to a Kalman filter to obtain the “trajectory” of the optimal solution.

  Another approach to overcoming the linearization problem on the ground involves formulating a set of equations as a nonlinear minimization problem (specifically, as a weighted nonlinear least squares problem). Specifically, the nonlinear objective function to be minimized is

Is defined. The weight W _i is selected to be inversely proportional to the SNR of the measured distance R _i . The best estimate of receiver location is obtained as a set of (X, Y, Z, Δt) that minimizes the objective function. When barometers or other altitude aids are available, the objective function is

Changed to

  Position resolution based on this method becomes more stable and robust, especially under small-sized ground system configurations. With this configuration, small changes in receiver coordinates can cause large changes in the observation matrix, and sometimes linearized iterations do not converge. Convergence or divergence to a local minimum more often occurs due to a residual bias in the measurement that affects the shape of the objective function, so that a local minimum can exist. Residual bias can be very common in indoor / urban canyon environments. The above nonlinear equations make the position algorithm robust against measurement bias, in addition to overcoming the small shape linearization problem.

  One approach to performing the minimization of the function f to obtain the optimal X, Y, Z is to use a genetic algorithm (such as differential evolution) to find the global minimum of the function. The use of such an algorithm allows the solution to avoid local minima that occur with small shape ground positioning when multipath bias is present in distance measurements.

  Regardless of whether linear least squares or non-linear least squares is used to solve the pseudorange measure, it is important that the quality metric is provided along with the position estimate. The position quality metric must be a function of the pseudorange metric residual, the quality of the measurement, and the shape of the tower relative to the estimated position. The pseudorange measurement residual of the i-th tower measurement is

Given by. The average weighted rms pseudorange residual is

Given by. HDOP, VDOP, and PDOP are obtained from diagonal elements of H = (A ^T A) ⁻¹ A ^r

Is defined. The pseudorange RMS (root mean square) error at a particular SNR is

Given by. Here, f is generally a nonlinear monotone decreasing function of its argument. The function f can be analytically derived for a particular receiver configuration as a function of the signal BW and the receiver BW, or alternatively can be found from simulation as a table that maps SNR to distance error.

  The 2D location quality metric is

Is defined. Similarly, the altitude and 3D location quality metrics are

Given by. The quantity α is selected based on the desired level of confidence. For example, a value of 3 is used to obtain 95% confidence and a value of 1 is used for 68% confidence.

  Another method of positioning using a WAPS system involves the use of a WAPS reference receiver in a differential manner. A time-stamped reference receiver measurement, along with the latitude, longitude, and altitude of the WAPS tower and reference receiver, as shown in the “Differential Global Positioning System” and discussed in the context of timing synchronization, It can be used to determine the timing delta during the WAPS tower transmission at the time stamp. After the timing delta between the transmitters is known, the distance equation can be reduced once again to have a single common time bias. The WAPS receiver can then avoid demodulation of the WAPS data stream (eg, to extract timing corrections from the data stream). The WAPS receiver measurements can be sent to the server and then the location can be calculated at the server or, alternatively, the reference receiver measurements can be relayed to the WAPS receiver. The position can be calculated there. Assume that the latitude, longitude and altitude of the WAPS tower are already known / available for use in position calculations. When the WAPS data stream is protected, the difference system can avoid the need to extract data from the protected data stream for timing correction purposes.

  Another alternative method for obtaining positioning from a WAPS system uses RSSI fingerprinting techniques. A database of WAPS tower transmit power / location and RSSI levels is built for a given target area based on training measurements within the area where positioning is required. Note that the RSSI database can also be augmented with angle of arrival (AOA) information to improve the solution. The WAPS receiver RSSI measurements (and possibly AOA measurements) are then used to look up this database to obtain location estimates. An alternative method of using a WAPS RSSI measurement is to use a propagation model (or simple extrapolation / interpolation technique) to convert the measurement into a distance estimate and then triangulation to determine position Is to use. Note that RSSI measurements in these fingerprinting techniques can be replaced by any other measurement that can be converted to distance.

  An alternative method of calculating position using the WAPS infrastructure uses a blind method of obtaining a position from the WAPS system without prior knowledge of the WAPS tower location. In this way, the approximate location of the WAPS tower is determined by field measurements (eg, measuring RSSI from multiple angles around the WAPS tower at a GNSS tagged location and then estimating the WAPS tower location. (By using a weighted average based on the RSSI of these locations). Thereafter, any of the RSSI fingerprinting methods can be used to determine the location (eg, as described in the above paragraph).

  An alternative method of calculating the location using the WAPS infrastructure can be used to calculate the location offline. The position calculation includes storing a sample segment of the WAPS signal from the WAPS receiver, optionally with an approximate position and a WAPS time tag (eg, the stored data is I data or baseband at low IF) IQ data at the same time). Note that it is sufficient to store enough samples to be able to acquire a signal. The sample is later processed to retrieve, obtain and calculate the distance to the WAPS tower. This method can use offline data to look up tower location and timing correction information that can be stored in a central database on the server. This method of offline location calculation provides the ability to support WAPS positioning at the cost of memory only on the device. Another benefit of this method is that it takes a very short time to store the WAPS IQ data, so it requires quick tagging of the location, but is useful for applications where the exact location is not instantaneously required. It will be something. One possible application of this method may relate to photographic geo-tagging.

Another approach to positioning uses carrier phase measurements in addition to the code phase measurements shown above. Carrier phase measurement
φ _i (t ₀ ) = r _i (t ₀ ) + N _i λ + Δt
Can be written. Various techniques can be used to resolve the integer ambiguity N _i in the carrier phase measurement. Code phase measurements, measurements at multiple frequencies, and / or other methods can be used to resolve ambiguities. Thereafter, the carrier phase measurement at time t _k can provide accurate tracking of the position at which to start the correct initial position. The carrier phase measurement at a future time,
φ _i (t _k ) = r _i (t _k ) + N _i λ + Δt
Can be written.

As long as the carrier phase measurement does not have a cycle slip, N _i is not changed (i.e., the signal must be tracked using a continuous phase lock), the new location is calculated using the least square method be able to. Alternatively, these measurements can be used in a Kalman filter to update the new position state. If phase lock is lost, a new value of integer ambiguity needs to be calculated.

  Another approach uses differential positioning relative to the reference receiver described above. Differential positioning can be performed using either sign measurements, carrier measurements, or a combination of both. A single differential observable is

Is calculated for the code and carrier phase by subtracting the same tower measurements from the reference receiver r and receiver s.

  Note that all timing errors at the transmitter do not appear in these observables, thus allowing position resolution even when the system is asynchronous or incompletely synchronized. In addition, all tropospheric delay errors in the measurement are almost offset, since the troposphere delay is likely to correlate in the local area for a baseline with a short troposphere delay (eg, the distance between reference receiver r and receiver s). To do. The communication channel is used to transmit distance measurements and carrier measurements from the reference receiver r to the receiver s for position calculation. Alternatively, receiver s and receiver r need to communicate distance and carrier to the server for position calculation.

  With any location solution, the height of the receiver can be determined using topographic map placement or barometric pressure sensing. Using the map placement, during trilateration, the user's location can be constrained to be on the terrain based on the terrain database, and the user's height is determined. The user's height can also be constrained to be within a certain height above the terrain. For example, the maximum altitude above the terrain can be constrained based on the tallest building in the area. This type of constraint can improve the quality of the height solution (eg, by removing ambiguous solutions that are sometimes created when using biased distance measurements).

  In addition, when an indoor building map is available, the information (along with associated constraints at possible user locations) can be used to assist in position resolution. For example, physical constraints can be used to constrain the user motion model, thereby improving the quality of the tracking Kalman location filter. Another use of building maps is to determine / estimate the quality of distance measurements for a particular tower based on the physical environment from the tower to the indoor location. A better estimate of distance quality can be used to weight a position calculation that leads to a better position estimate.

  When using a barometric sensor, the calibrated barometric sensor can be used to measure the pressure differential as the receiver terminal is moved up or down at altitude. This is compared to a calibrated value or average value of pressure at different altitudes to determine the height of the receiver.

Receiver alignment based on measurement consistency checking when more measurements are available than the minimum required 3 measurements for a two-dimensional position when calculating a position solution Sex monitoring is used to exclude “outlier” measurements. “Abnormal” measurements may be due to channel effects such as loss of timing synchronization or multipath at the transmitter.
Altimeter-Based Approach for Determining Altitude The WAPS system of one embodiment includes an altimeter (pressure sensor) that assists in determining user elevation. The only information available from the pressure sensor is the atmospheric pressure at the time and place of measurement. In order to translate this into an estimate of the sensor elevation, a plurality of additional information is required. The standard formula for associating pressure with elevation based on the weight of the air column is:

Here, z ₁ and z ₂ are two elevations, P ₁ and P ₂ are the pressures at these elevations, and T is the temperature (in K units). R = 287.052 m ² / Ks ² is a gas constant, and g = 9.80665 m / s ² is an acceleration caused by gravity. Note that this equation provides relative information for determining the difference in elevation with respect to the pressure difference. This equation is generally used with z ₂ = 0 so that P ₂ is sea level pressure. Since sea level air pressure varies greatly with weather conditions and location, sea level pressure is required in addition to the temperature and pressure at the site where elevation is determined. It can be seen that a 1 m increase in elevation corresponds to a 12.01 Pa decrease in pressure when applying standard atmospheric conditions of T = 15C and P = 101325 Pa.

  Therefore, in order to determine the altitude with a resolution of 1 m, the sea level pressure must be known with an accuracy much finer than 36 Pa. Since T is measured in Kelvin, it is worth noting that an error of 3 ° C. (or K) in temperature corresponds to an error of about 1% in elevation. This can be large when determining higher elevations above sea level and when trying to resolve higher floors in tall buildings. Therefore, a pressure sensor with high accuracy and resolution is required to determine altitude with 1 m resolution. To fit within a mobile device, these sensors must be low cost, low power, small size. Note that commercial weather grade sensors do not provide this level of accuracy or resolution and are not updated at the rate required to determine elevation.

  The key to determining altitude with an accuracy of 1 m is to have a system that provides sufficiently local and sufficiently accurate reference pressure information. This system must be able to provide measurements close to unknown locations in temperature, close in distance and time, and ultimately be accurate enough to capture changing weather conditions. Thus, an elevation determination system in one embodiment includes a mobile sensor that determines the pressure and temperature of an unknown location with sufficient accuracy, and a pressure and temperature of a known location that is sufficiently accurate and sufficiently close to the unknown location. Enter an array of reference sensors to determine and all reference sensor data, reference sensor locations, and other augmenting information to generate an accurate reference pressure estimate at that location in the WAPS network Including, but not limited to, an estimation algorithm and a communication link between a reference sensor and a mobile sensor to provide reference information in a sufficiently timely manner. Each of these elements is described in detail below.

  FIG. 27 is a block diagram of a reference elevation pressure system, under an embodiment. In general, a reference elevation processing system or reference system includes a reference sensor array that includes at least one set of reference sensor units. Each set of reference sensor units includes at least one reference sensor unit positioned at a known location. The system also includes a remote receiver that includes or is coupled to an atmospheric sensor that collects atmospheric data at the location of the remote receiver. A positioning application running on the processor is coupled to or a component of the remote receiver. The positioning application uses the atmospheric data and the reference data from the reference sensor unit (s) of the reference sensor array to generate a reference pressure estimate at the location of the remote receiver. The positioning application uses the reference pressure estimate to calculate the elevation of the remote receiver.

  More specifically, the reference elevation pressure system includes a mobile sensor that determines with sufficient accuracy the pressure and temperature at an unknown location, the mobile sensor being a component of or coupled to a remote receiver. The The system includes a reference sensor array that includes at least one reference sensor unit that accurately determines pressure and temperature at a known location appropriate to the location of the remote receiver. The reference sensor unit communicates with a remote receiver and / or an intermediate device (eg, sensor, repeater, etc.) (not shown) to provide reference information. The system, in one embodiment, inputs all reference sensor data, reference sensor location, and other augmenting information to generate a relatively accurate reference pressure estimate at that location. Includes a positioning application, which is an estimation algorithm. The positioning application can be a component of the remote receiver, hosted on a remote server or other processing device, or distributed between the remote receiver and the remote processing device.

  FIG. 28 is a block diagram of a WAPS integrating a reference elevation pressure system, under an embodiment. As described herein, WAPS receives and tracks (and optionally has a location calculation engine) a network of synchronized beacons, beacons and / or global positioning system (GPS) satellites. And a server containing a tower index, billing interface, and proprietary encryption algorithm (and optionally a location calculation engine). This system operates in a band of licensed / unlicensed operation and transmits proprietary waveforms for location and navigation purposes. The WAPS system can be used in connection with other positioning systems or sensor systems to provide a more accurate location solution. Use the remote receiver elevation calculated using the reference pressure estimate either explicitly as an altitude estimate or implicitly to help position calculation in any position location system Note that you can.

  One example system integrates a reference elevation pressure system with WAPS. In general, an integrated system includes a terrestrial transmitter network that includes a transmitter that broadcasts a positioning signal that includes at least a ranging signal and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. The system includes a reference sensor array that includes at least one reference sensor unit positioned at a known location. The remote receiver includes or is coupled to an atmospheric sensor that collects atmospheric data at the location of the remote receiver. A positioning application running on the processor is coupled to or a component of the remote receiver. The positioning application uses the atmospheric data and reference data from the set of reference sensor units in the reference sensor array to generate a reference pressure estimate at the location of the remote receiver. The positioning application uses the reference pressure estimate and information derived from at least one of the positioning signal and a satellite signal that is a signal of a satellite-based positioning system to determine the position of the remote receiver including the elevation. calculate.

  More specifically, the integrated system includes a mobile sensor that determines pressure and temperature at an unknown location with sufficient accuracy. The mobile sensor is, but is not limited to, a remote receiver component. The system includes a reference sensor array that includes at least one reference sensor unit that accurately determines pressure and temperature at a known location appropriate to the location of the remote receiver. The reference sensor unit communicates with a remote receiver and / or an intermediate device (eg, sensor, repeater, etc.) (not shown) to provide reference information. The reference sensor unit can be co-located with one or more WAPS transmitters and / or can be separately located at other known locations. The system, in one embodiment, is an interpolation-based estimation algorithm that inputs all reference sensor data, reference sensor location, and other augmenting information and generates a reference pressure estimate at that location. Includes positioning application. A positioning application can be a component of a remote receiver, hosted on a WAPS server or other processing device, or distributed between the remote receiver and the WAPS server.

  As noted above, the mobile sensor must be able to determine pressure with resolution and accuracy much finer than 36 Pa. Many pressure sensors have built-in temperature sensors to provide compensation for non-ideal sensor performance, but due to the self-heating effect, these sensors are sufficiently accurate measurements of external air temperature. May not provide. Even if accurate sensors are not commercially available, if sensors with adequate resolution are available, they can be used for altitude estimation at the floor level. The mobile sensor of one embodiment determines the reference pressure data with a resolution of less than about 36 Pascals and the temperature data with a resolution of at least one less than or equal to about 3 degrees Celsius.

  These sensors have inherent short-term and long-term stability issues that can be corrected by moderate filtering techniques such as averaging two to three samples. Each sensor may have an offset that can vary with temperature, for example, which needs to be calibrated or compensated by a look-up table.

  With sufficient calibration, these sensors must provide the required accuracy. Some sensors may be sensitive to high speed motion. Several heuristic rules can be used to limit the use of pressure information when high velocities or accelerations are observed. However, high speeds are rarely experienced in indoor environments. When traveling at high speeds, GPS positioning and map data typically provide sufficient vertical position information.

  Note also that the sensor must be mounted in a manner that is exposed to outside air but not exposed to wind, ventilation, or other air movement. The mounting or positioning of regular consumer products inside must yield acceptable results. The battery compartment and connector provide an indirect path for external air to reach the sensor while preventing any direct air movement. However, a waterproof device should require special preparation to give the sensor external access.

  The reference sensor is deployed in a much smaller volume at a dedicated location, so a relatively good accuracy can be obtained within the reference system, and a large overall error budget can be obtained with the mobile sensor. It becomes possible to assign to. Existing markets for absolute pressure sensors, such as weather altimeters and aircraft altimeters, do not have the same high accuracy requirements as the application of one embodiment. In the reference application, one embodiment uses multiple sensors for both redundancy and improved accuracy through measurement averaging. In addition, the sensor can be packaged to limit the temperature range over which the sensor is exposed and optimally calibrate the sensor for this limited temperature range.

  The reference system must average or otherwise filter the individual measurements to improve accuracy on a time scale on the order of 2-3 seconds to 2-3 minutes. The height of the reference sensor must be measured with an accuracy of “cm” level, the outdoor temperature must be continuously measured and logged, and the sensor measures the barometric pressure. Must be exposed to the outside air but should not be exposed to wind, drafts, or other large air movements (use baffles or other packaging to direct air along the indirect path to the sensor The sensor must not be sealed within the waterproof enclosure, as the waterproof enclosure may interfere with the measurement of ambient pressure. The reference sensor of one embodiment determines reference pressure data with a resolution of less than about 36 Pascals and temperature data with a resolution of at least one less than or equal to about 3 degrees Celsius.

  One embodiment enables interpolation-based reference pressure estimation. Given the pressure and temperature measurements at each WAPS transmitter tower and the tower location and other augmenting information, one embodiment uses sea level atmospheric pressure at the mobile user location as a reference value for user height estimation. Predict. Thus, an atmospheric pressure gradient model is generated, and the pressure measurements at each tower site serve as sample data for local changes in this model. This estimation algorithm therefore calibrates the reference pressure accuracy at the user location, comparable to the direct measurements taken at the beacon tower.

  A description of this interpolation formulation will be given below. Within one of the WAPS networks, given a reference atmospheric pressure sensor with n transmitter towers, an equivalent sea level atmospheric pressure is estimated based on the reference sensor output. This is done in two steps, but is not limited thereto.

The first step is given the reference sensor height h _i (in meters) above the sea level at transmitter tower i and the pressure reading p _i (in pascals) and temperature reading T _i (in Kelvin units) from the reference sensor. Thus, the equivalent sea level atmospheric pressure P _i (in pascals) is calculated at a location having latitude x _i and longitude y (in degrees) _i using the equation below.

Here, g is a gravitational acceleration constant, and R is a specific gas constant of air. As a second step, after calculating the equivalent sea level atmospheric pressure at all n transmitter locations of the WAPS network and obtaining the latitude information x ₀ and longitude information y ₀ of the user using WAPS, the equivalent sea level pressure is Estimated at user location P ₀ using the following equation:

Here, W _i = W _i (x ₀ , y ₀ , x _i , y _i ) is a weighting function that depends on both the user location and the reference site i location.

  The communication link of one embodiment provides information used by the mobile sensor. One embodiment broadcasts a pressure update every 2-3 seconds to once every 2-3 minutes, but is not limited to this.

  If the reference system broadcasts the reference information infrequently, the mobile unit receives the last information and continuously monitors the broadcast to store it if necessary before the next broadcast, a new Perform at least one of waiting for the next broadcast before calculating the elevation, or “pulling” or querying the reference system for the latest information when needed. The pull approach of one embodiment, where the reference system does not broadcast information, minimizes system bandwidth. But pull uses two-way communication between the reference system and the mobile, and since multiple reference sites are used for any mobile calculation, the mobile must query which reference site that mobile is It is necessary to determine whether or not. A good compromise for minimizing mobile monitoring while keeping latency low is to let the reference system broadcast data more frequently than it takes to update the measurements.

  One embodiment includes two possible approaches for information content. The first approach allows the mobile to perform all of the calculations, where the information transmitted by the reference is the reference location (latitude and longitude) with an accuracy of 1 meter, 0.1-0.2 m Reference sensor height with accuracy of, measured temperature at reference site (after some filtering), measured atmospheric pressure at reference site with accuracy of 1 Pa (filtering, sensor temperature compensation, and offset) Including, but not limited to, a measure of confidence) and after any other local calibration.

  Alternatively, the reference site can use its temperature and pressure measurements to calculate the equivalent sea level pressure. When this approach is used, the list of information that is broadcast is the reference location (latitude and longitude) with 1 meter accuracy, the height of the reference sensor with 0.1 to 0.2 m accuracy, Includes, but is not limited to, a calculated equivalent sea level pressure (with 1 Pa accuracy) at the reference site and a confidence measure.

One embodiment also reduces each bit of data transmitted, but broadcasts each of the data relative to some known constant. For example, the reference site may be relatively close to the mobile site and thus only transmit fractional degrees of latitude and longitude, assuming an integer part. Similarly, the atmospheric pressure is usually about 10 ⁵ Pascal, but only changes from 2 to 3000 Pa from the standard atmosphere. Thus, one embodiment broadcasts an offset from standard atmospheric pressure to reduce bandwidth versus broadcasting absolute pressure.

  Latitude and longitude obtained from GPS or similar systems are not particularly useful in urban applications. Instead, a database is needed to map latitude and longitude to street addresses. Elevation has similar limitations in the vertical dimension. A useful parameter is how many floors a person is on. This can be accurately determined from the elevation information when there is access to a database of ground level elevation and the height of each floor of the building. For low buildings up to about 3 floors, it may be sufficient to know the ground level elevation from a mapping or similar database and estimate the floor height. For higher buildings, more accurate information about floor height is needed.

  This presents an opportunity to implement a smart learning algorithm. For example, it can be assumed that a cell phone is carried between 1 m and 2 m from the floor. Thus, the system of one embodiment is capable of accumulating the elevation of multiple cell phones in a building, and this data is expected to be approximately 1.5 meters from each floor. If there is enough data, it is possible to develop confidence in the height of each floor in the building. Thus, the database can be learned and refined over time. Such an algorithm is more complex for buildings with mezzanine floors between ramps or floors, but can still generate useful data for the majority of buildings.

  Sensor offsets and potentially other parameters can be calibrated at the time of manufacture. This should be possible by cycling the sensor through a range of temperatures and pressures, along with a known good sensor that provides reference information. These calibration parameters are likely to drift slowly with age. Thus, one embodiment uses an algorithm to gradually update the calibration over time (eg, the algorithm recognizes when the sensor is stationary at a known height and under these conditions Update the calibration table).

  In addition to the general application of determining a person's location, one embodiment may include specialized applications that do not require absolute elevation information but use more accurate relative elevation information. For example, finding a firefighter who has fallen in a building requires that the position of the fallen person relative to the rescue team be accurately known, but the absolute position is not so important. Additional accuracy in relative positioning should be possible by having an extra manual step at the beginning of the application. For example, all firefighters can initialize their tracking device at a known location, such as the entrance of a building, before entering the building. Their position relative to that point, and therefore their position relative to each other, can be very high over a period of time, even if the absolute elevation is not accurate and cannot fully compensate for weather-related pressure changes. It can be determined accurately. Similarly, shopping-related applications that require higher accuracy than those available from absolute measurements can be implemented by having the user press a button at a known point in the mall. Their position relative to that point can be determined very accurately over a period of time.

  Alternatively, mobile beacons can be used as a local reference to provide greater accuracy at specific locations. For example, a shopping mall can have its own reference sensor to provide higher accuracy within the mall. Similarly, fire engines can be equipped with a reference sensor to provide local reference information at the fire site.

  Low cost pressure sensors have problems in that they have an offset from the correct reading. Experiments have shown that this offset is very stable on a time scale from weeks to months. However, this offset is likely to drift slowly with time over a period of months to years. It is simple to measure and compensate for this offset during manufacturing, but it is unlikely that the compensation will remain accurate over the life of the product. Therefore, a means for recalibration in the field is necessary.

  The sensor of one embodiment can be recalibrated when it is at a known elevation and the atmospheric pressure is known. This embodiment identifies a practical situation where the sensor is at a known elevation. For example, if the sensor is in a device with GPS capability and GPS satellites are being received with strong signal strength, the altitude derived by GPS must be very accurate. Accumulating deviations from GPS altitude over time under good signal conditions can provide an estimate of the correction required for sensor calibration.

  Similarly, the sensor system can learn user habits and use this information to later correct the calibration. For example, if the user consistently places her phone in the same place at night, the sensor may begin tracking altitude at this location, perhaps at a particular time, such as late at night. Initially, these values are accumulated and stored as the true altitude at that location. After several months, when the sensor determines that it is at the same location at the same time of the night, the sensor can begin to track the deviation from the true altitude previously determined. These deviations can be accumulated to slowly generate corrections for the calibration. These approaches also use the reference pressure measurements provided by the WAPS network because they also use current atmospheric pressure knowledge.

  A standard process for determining altitude from pressure readings involves converting the measured value at the reference location to an equivalent sea level pressure and then using this to determine the altitude of an unknown pressure sensor. The standard formula is

It is. Note that a minus sign has been added since the height is usually measured as positive away from the Earth's surface. Furthermore, the logarithm is corrected to “ln” because it is a natural logarithm. This equation relates the height z above the sea level to the atmospheric temperature (T) and pressure (P) at that point and the sea pressure (P ₀ ) below that point.

  One additional problem with the application of this equation is that the height is directly proportional to temperature, which is a measured quantity that is not exactly known. This means that a 1% error in temperature results in a 1% error in height. This is not a big problem when used near sea level. However, when this equation is applied in high buildings, especially in higher elevation areas such as Denver, a 1% error in height can be large when trying to resolve floor level elevation. There is. For example, the elevation of Denver is about 1608m. Thus, a 1% error in temperature results in a height error above sea level of 16m. This is almost 5 floors.

  One way to avoid this sensitivity to temperature accuracy is to recognize that the above equation is actually a relative equation. That is, this equation is

Where z ₁ and z ₂ are any two elevations, and P ₁ and P ₂ are the pressures at these elevations. It is only a matter of practice that z ₂ is set to 0 and therefore P ₂ is at sea level.

  Rather than using sea level as a reference point, any convenient elevation can be used. For example, the average altitude of a city is moderate or the average altitude of a reference sensor used to collect pressure data is useful. As long as a reference elevation is used that keeps the height difference small, the effect of temperature error is not significant. The only requirement is that all devices used in the system know what reference elevation is being used.

The elevation (z) of a point on the earth, the atmospheric pressure (T) and pressure (P) at that point, and the sea pressure (P ₀ ) below that point,

There is a standard formula that relates as This equation assumes that there is an air column of constant temperature between the sea level and the point. Thus, the sea level pressure used is a virtual component and may not necessarily be the actual pressure at the sea level because the point in question may not be near the true sea level.

A standard process for determining the elevation of an object is a two-step process. First, sea level pressure is, and measuring the temperature and pressure at the point of known elevation, are then determined by the method comprising the inverse of this equation to solve for P _0. Next, the temperature and pressure at the point of unknown elevation are measured and this equation is applied to determine the unknown elevation.

  Implicitly included in this process is that the only parameter of interest is that of the same horizontal location, as is typical for aircraft approaching a landing field that uses measurements at the landing field with respect to the reference. The assumption is that it is the height of another object above. Typically, those interested in determining height for other purposes have extended this concept to determine height that is generally near the reference location but not directly above it. This expansion assumes that the sea level pressure does not change between the relevant location in the vicinity and the reference location.

  This process therefore has three assumptions. The first assumption is that the temperature is constant from the reference location to the virtual sea level below it. The second assumption is that the temperature is constant from that point to the virtual sea level below it. The third assumption is that the sea level pressure is the same at the reference location and the point. However, since sea level pressure is temperature dependent, assuming that the sea level pressure is the same at the two locations implies that the temperature is the same at these locations. Therefore, if different temperatures are measured at the reference location and the point in question, one of these assumptions is violated. Measurements have shown that there are temperature and pressure differences that can be significant for elevation determination, even over a distance of 2-3 kilometers.

  The constant temperature assumption over elevation changes at a given location is part of the atmospheric equilibrium model and is probably necessary. The only alternative would be a complete dynamic model of the atmosphere, including the effects of wind, surface heating, convection, and turbulence. Atmospheric data imply that the constant temperature model is a very good approximation at altitudes below 1 km, at least on long distance scales. At higher elevations, a linear reduction rate is often applied.

  One embodiment relaxes the assumption of constant sea level pressure between the reference location and the point in question. The first approach of one embodiment employs the sea level pressure at the reference location determined as above, but further applies the ideal gas law to convert it to sea level pressure at standard temperature. It is then assumed that this sea level pressure at the standard temperature is the same at that point. The temperature at the new location is used to convert this to sea pressure at that location, and then the above equation is applied to determine the elevation.

  The second approach of one embodiment uses a network of reference locations to determine the variation in equivalent sea level pressure with horizontal locations in real time. The plurality of measured values are then combined to determine the best estimate of sea level pressure at that point. There are at least two possible ways to determine the best estimate: a weighted average technique where the weight is a function of the horizontal distance from a particular reference point to that point, and the calculated sea level pressure at the reference location And a least-squares fit to create a secondary surface that can be used to supplement the estimate of sea level pressure at that point.

  The two methods described above can also be combined. That is, at each reference location, the sea level pressure at standard temperature is determined and these data are combined using one of the above techniques to obtain the sea level pressure at standard temperature at that point. Generate the best estimate.

  Further, when using an altimeter, one embodiment uses the application level data to a hardware or software filter that operates continuously on location and altimeter data, thereby changing the condition of the air conditioner ( Recognize sudden movements of pressure, such as being turned on) or opening a car window.

  In addition, an anemometer can be used in a beacon to determine the direction of wind flow, which is considered an indicator of atmospheric pressure gradient. An anemometer can be used with a compass to determine the exact direction and level of the wind flow, and this direction and level can be used to compensate for user sensor variations and / or by a filter. Can be removed.

  The height of each floor of a given building can be determined by various methods including, but not limited to, the user walking through the building through stairs and collecting information about each floor, ramp, etc. . In addition, an electronic diagram can be used to determine the relative height of each floor.

  When height is estimated based on either WAPS or altimeter, information such as terrain, building height, surrounding building height, etc. can be used to constrain the height solution .

  Along with the historical reference pressure data collected from the reference sensor over a long period of time (days, months, years), after the average pressure is known at a given location, it can be used to The height can be determined predictably based on the pressure at the location (without calibration or user input).

  In one embodiment, the user's height can be calculated on the remote server by using data from the user's sensor and combining it with data from the reference sensor. In this way, other information such as building information, crowdsourced information, etc. can also be used to determine the user's exact altitude.

  If a user is very close to another user whose height is known, this information can be used to determine the height of the unknown user.

  In one embodiment of the network, the reference sensor need not be co-located with the WAPS beacon. A finer or coarser grid of independent sensors with a data connection to the server can be used for reference pressure measurements. The centralized server can either send reference pressure information to the mobile or instruct the transmitter about data that needs to be sent to the mobile as part of the WAPS data stream.

  In another embodiment, the WAPS system uses additional simplified beacons (supplemental beacons) that provide additional sensor information such as pressure, temperature, etc. in smaller areas such as buildings. This transmission can be synchronous or asynchronous with respect to the main WAPS timing beacon. In addition, the supplemental beacon uploads the sensor data to a centralized server from which the sensor data is disseminated to the mobile unit or transmits that data over a predefined set of PRN codes that can be demodulated by the WAPS mobile receiver. Either can be done.

  The reference pressure network can be optimized based on accuracy requirements and historical pressure variation data for a given local area. For example, a reference sensor can be deployed in the building or mall when very accurate measurements are required.

  The WAPS beacon network, together with reference pressure data, forms a closed network of accurate pressure and temperature measurements with very short time intervals that can be used by other applications such as geodesy.

  The rate of change in pressure combined with data from other sensors can be used to determine a vertical velocity that can be used to determine whether the user has advanced through the elevator. This can be very useful in emergency situations and / or tracking applications.

For sensors with a lower resolution than that required to estimate the floor height, use the averaging of pressure measurements over time under static conditions and use the user height based on the reference data. You can get it.
Hybrid positioning and information exchange with other systems The system of an embodiment can be combined with any “opportunity signal” to provide positioning. Examples of opportunity signals include GPS receivers, Galileo, Glonass, analog or digital TV signals, signals from systems such as MediaFLO, Wi-Fi, FM signals, WiMax, cellular (UMTS, LTE, CDMA, GSM, etc. ), Bluetooth, and one or more of LORAN and e-LORAN receivers.

  Regardless of the signal type, the opportunity signal provides a surrogate for distance measurement, such as distance measurement or signal strength. This surrogate for distance is appropriately weighted and combined to obtain a location estimate. The weighting can use the signal-to-noise ratio (SNR) of the received signal or, alternatively, a metric that defines the receiver environment (eg, urban, suburban, local, from assistance data) Based on environmental knowledge, input from the application, whether the receiver is indoors or outdoors). This is typically done in environments where the system of the embodiment is unavailable or where signal coverage is limited. When using SNR as the weight for a particular measurement, the weight is simply an inverse function of SNR (or more) to allow an optimal combination of WAPS measurements as well as other system measurements to obtain position. Any other function that provides lower weight for signals with low SNR). The final positioning solution can be obtained by taking distance measurements from additional signal sources, combining with WAPS distance measurements, deriving position solutions for latitude, longitude and altitude, or by additional sources / Taking position measurements from the device and position measurements from the WAPS system and providing an optimized location solution using a combination of these location measurements based on position quality metrics from different systems; Can be calculated by either Various configurations for obtaining a hybrid solution using WAPS measurements / WAPS position estimates are shown in FIGS. 29, 30 and 31. FIG. Any of the architectures described below can be selected for use depending on the hardware and software partition of the system.

  FIG. 29 is a block diagram of hybrid position estimation using distance estimates from various systems, under an embodiment. Distance measurements (along with associated distance quality metrics) are used from GNSS and other positioning systems and combined into a single optimal position solution by a hybrid position engine. This architecture is optimal with respect to using data that can be used to obtain the best position estimates from them.

  FIG. 30 is a block diagram of hybrid position estimation using position estimates from various systems, under an embodiment. Independent position estimates from different systems are used to select the one with the best quality along with the position quality. This architecture is easiest to implement and integrate because the different positioning systems are well separated.

  FIG. 31 is a block diagram of hybrid position estimation using a combination of distance and position estimates from various systems, under an embodiment. For example, the position estimate from the WLAN positioning system can be compared with the position estimate from the distance measurements from the GNSS and WAPS systems to reach the best solution.

  Location aid information (loosely coupled) to the WAPS system for use in tracking mode using inertial navigation sensors (INS) such as accelerometers and gyros, magnetic sensors such as e-compass, and pressure sensors such as altimeters Or raw sensor measurements (referred to as tight coupling) can be provided.

  An accelerometer can be used in the receiver of an embodiment to determine the frequency of updating location reports to the server. A combination of a position solution and a sequence of accelerometer measurements can be used to detect static position, constant velocity, and / or other movement. This movement data or information can then be used to determine the frequency of updates, for example, when there is uneven motion, the update frequency can be set to a relatively high frequency, and the receiver When is at a constant rate or stationary for a predetermined time period, the frequency of updates can be reduced to save power.

  Sensor or position measurements can be combined into a position solution with a position filter (such as a Kalman filter). Two types of tightly coupled architectures in which sensor measurements are combined with GNSS and WAPS measurements in a WAPS hybrid position engine are shown in FIGS. FIG. 32 illustrates a position / velocity estimate from a WAPS / GNSS system to help calibrate the drifting bias of the sensor when the quality of the GNSS / WAPS position and / or speed estimate is good, under an embodiment. 5 is a flowchart relating to determination of a hybrid position solution in which is fed back. This architecture simplifies algorithm formulation by separating the sensor calibration and position calculation portions of the algorithm. However, a drawback of this method is the complexity in determining when it is a good time to recalibrate the sensor using the WAPS / GNSS estimate.

  FIG. 33 illustrates that sensor parameters (bias, scale, drift, etc.) are estimated as part of the position / velocity calculation within the GNSS unit and / or WAPS unit, without the need for explicit feedback, under an embodiment. It is a flowchart regarding determination of a hybrid position solution. For example, sensor parameters may be included as part of a Kalman filter state vector used to track receiver position / velocity. This architecture provides an optimal solution in that the information is used in one combined filter to update both position and sensor parameters.

  The loose coupling that the selection unit selects between the position estimate from the GNSS engine and the position estimate from the WAPS engine is shown in FIGS. Note that the selection unit can be part of a WAPS location unit or a GNSS location unit. FIG. 34 is a flow diagram for determining a hybrid position solution in which sensor calibration is separated from individual position calculation units, under an embodiment. FIG. 35 is a flow diagram for determining a hybrid position solution in which sensor parameter estimation is performed as part of the state of individual position calculation units, under an embodiment.

  Loosely coupled methods are generally worse than tightly coupled methods because the selection uses only information from one system. Among the loosely coupled or tightly coupled methods, the method uses distance along with raw sensor measurements to determine position, and the sensor parameters in one optimal filter are sensor parameters and positions separately. Better than calculated. Consequently, the preferred method from a performance perspective is a tightly coupled system with implicit sensor parameter estimation. However, depending on the partition of the hardware / software platform, one or more of these methods can be easily implemented and selected for that reason.

  Information can also be exchanged between the WAPS system and other transceiver systems (cell phones, laptops, PNDs, etc.) on the same platform. The transceiver system may be, for example, a Bluetooth transceiver, a WLAN transceiver, an FM receiver / transmitter, a digital TV system or an analog TV system, a satellite communication system such as MediaFLO, XM Radio / Iridium, GSM / UMTS / cdma2000 1x / EVDO or WiMax. Can be a cellular modem transceiver). FIG. 36 illustrates the exchange of information between the WAPS system and other systems, under an embodiment. The exchange of information between systems can improve the performance of either system. Since the WAPS system time is aligned with GPS time, the WAPS system can provide good quality timing and frequency estimates for any other system. Time estimates and frequency estimates to the WAPS system can reduce the WAPS acquisition search space in code and frequency. In addition, the WAPS system can provide location information to other transceiver systems. Similarly, when other systems have usable location information (partial position, eg altitude or 2D position, or complete position, eg 3D position or raw distance / pseudo distance / distance difference) The location information can be provided to the WAPS system with or without a location quality metric. The distance / pseudo-range data together with the transmitter location (or other means of calculating the distance from the transmitter location to any receiver location) to allow the use of this distance information in a hybrid solution Must be provided. The distance difference corresponding to the two transmitters must be provided along with the location of the two transmitters. The WAPS system uses this information to assist in its location resolution. Alternatively, location information can be provided in the form of a distance (or pseudorange) from a known transmitter location to the receiver device. These distances (or pseudoranges) are combined with the WAPS distances by a positioning algorithm to calculate the hybrid position.

  Examples of specific systems and the information that can be exchanged between them are shown in FIGS. 37, 38 and 39.

  FIG. 37 is a block diagram illustrating the exchange of location estimates, frequency estimates, and time estimates between an FM receiver and a WAPS receiver, under an embodiment. Location estimates from the WAPS system can be provided to the FM receiver. This location estimate can then be used, for example, to automatically determine active FM radio stations in the local area. The FM signal can also include RDS-Radio Data Service) transmission. The location of the FM station is an RDS / RBDS data stream (eg, Location and Navigation (LN) feature that provides data about the transmitter site, provides city and state names, and provides DGPS navigation data) This information can be used to provide location aids to the WAPS receiver. The frequency estimate from the WAPS system can easily be used to reduce the FM receiver tuning time for a particular station. In the other direction, the frequency quality of the estimate at the FM receiver is based on the FM radio station transmission quality. The time estimate in the WAPS system is based on GPS time, and the time can be transferred to the FM receiver to assist in timing alignment. The clock time (CT) feature in the RDS / RBDS transmission can be used to determine relative timing for the RDS data stream and can be forwarded to the WAPS receiver.

  FIG. 38 is a block diagram illustrating the exchange of location estimates, time estimates, and frequency estimates between a WLAN / BT transceiver and a WAPS receiver, under an embodiment. In general, these WLAN / BT transceivers do not have accurate frequency estimates, and as a result, the frequency estimates are very coarse and thus such estimates from the WLAN / BT transceiver to the WAPS receiver. Transfer of values may have limited value. In the reverse direction, the WAPS frequency estimate can reduce the time required for frequency acquisition on the WLAN system. For example, timing information extracted from a time stamp on a wireless LAN AP (access point) beacon can be transferred to the WAPS system to assist in acquiring the WAPS. Note that a reference with WLAN timing relative to GPS time is required to make this useful for the WAPS system. Similarly, if the WLAN / BT system has a usable location estimate (partial position, eg altitude or 2D position, or full position, eg 3D position or raw distance / pseudorange) The location information can be provided with or without a location quality metric for the WAPS system. The WLAN position estimate can simply be the geolocation of a nearby serving AP or other “audible” AP. The WLAN location estimate may be partial, for example, an altitude estimate based on the floor of the AP in question. WLAN location information may be a distance estimate for a known transmitter AP location (eg, the WLAN system may use a round trip time measurement to determine the distance estimate) or between two transmitting APs. It can also be a distance difference estimated value.

  FIG. 39 is a block diagram illustrating the exchange of location estimates, time estimates, and frequency estimates between a cellular transceiver and a WAPS receiver, under an embodiment. Better location estimates from cellular systems (partial, complete or raw distance / distance differences) (such as from FL or RL based positioning methods of TDOA, AFLT, or other similar cellular signals) These measurements can be provided to a WAPS system that uses these measurements to obtain position estimates. Frequency estimates from the cellular modem frequency tracking loop can be provided to the WAPS system to reduce the frequency search space and thus improve the WAPS acquisition time (ie, TTFF). Time estimates from the cellular system can also be provided to the WAPS system to reduce the code search space or to assist bit and frame alignment. For example, systems synchronized to GPS time, such as cdma2000 / 1x EVDO, can provide fine time estimates to the WAPS system, but asynchronous (such as GPS transmission such as GPS, etc.) such as GSM / GPRS / EGPRS / UMTS. A cellular system (not well synchronized to the time scale) can provide a coarse time estimate.

  Since the WAPS system time is aligned to the GPS time, the WAPS system can provide good quality timing and frequency estimates for any other system, even when not on the same platform. . For example, using a WAPS system, a pico / femto via periodic hardware signals such as pps (pulses per second) aligned with GPS second boundaries or a single pulse signal with an associated GPS time. Timing information can be provided to the cell BTS.

  As described above, the spectrum used by an embodiment of the WAPS system may include licensed or unlicensed bands or frequencies. Alternatively, the WAPS system can use a “white space” spectrum. A white space spectrum is defined as any spectrum in which the WAPS system senses or determines that it is free in the local area (not limited to TV white space) and transmits a location beacon within that spectrum. The transmitter of one embodiment is spectral sensing to detect unused spectrum and / or to communicate geolocation (which can be easily obtained from a GPS timing receiver) to a centralized database that adjusts the spectrum. Technology can be used. The receiver can include spectrum sensing techniques to listen to these beacons, or, in another embodiment, can be notified of the frequency to be tuned using a communication medium. The WAPS system can be adapted to dynamic white space availability or allocation (transmitted to a centralized database that allocates either the spectrum to be transmitted and / or the time duration that needs to be transmitted). If requested to broadcast instrument geolocation). A WAPS system can broadcast continuously on this spectrum, or it can share the spectrum with other systems as controlled by a centralized coordination service for the spectrum. The chipping rate and data rate of the WAPS system component can be dynamically changed to suit accuracy requirements and / or signal power and bandwidth availability at any given time. System parameters can be sensed by the receiver or can be communicated to the receiver via a communication medium. The transmitter can form a local network, or it can form a continuous network in the case of spectrum availability in a larger geographical area.

  The transmitter of one embodiment can coexist with other networks on the same transmission system in a time-sharing manner. For example, the same spectrum can be used in a time-sharing manner between the location application and the smart grid application. The transmitter is a broadcast transmitter that uses the maximum available power level and can dynamically adjust its power level based on spectrum sensing or as requested by a centralized coordination server. The receiver can use spectrum sensing, or it can communicate to the receiver about the current system parameters and wake-up time via a communication medium (which can also be a white space spectrum).

  Based on spectrum availability, the WAPS system of one embodiment can use one channel of TV white space (6 MHz bandwidth), or better multipath resolution when multiple channels are available. Multiple frequency bands can be used. If adjacent channels are available, channel bonding (eg, combining adjacent channels) can be used. The increased bandwidth can be used for better multipath resolution, higher chipping rates for higher accuracy, etc. Alternatively, the available bandwidth can be used under FDMA to help solve the near-far problem and / or multipath resolution.

  White space transmission / reception of a WAPS waveform in multiple white space bands may allow a better and faster integer ambiguity resolution for the WAPS carrier phase measurement. This allows for single point positioning with relatively high accuracy (on the order of less than one wavelength) using WAPS.

  The white space bandwidth can also be used as a communication channel in WAPS (if a reference receiver is used) between the reference receiver at the investigated location and the receiver whose position is to be found.

  When a licensed in-band WAPS system is available in the wide area network, the tower's white space based local network can be used to enhance the location accuracy of the WAPS receiver. The receiver can be designed to listen to both frequencies simultaneously or switch between licensed and white space bands and tune to the appropriate frequency.

  The white space band can also be used to send assistance information to the WAPS, GPS or AGPS system for other assistance information such as location aids and clock bias, satellite ephemeris, etc.

When multiple frequencies with wide separation are available, a WAPS system can be designed to take advantage of frequency diversity to provide better multipath performance.
Correlator Implementation With any CDMA receiver (or a receiver that uses a pseudo-random code as part of the transmitted bitstream), the correlation of the received signal with its PRN code is essential. The more parallel correlation that can be performed, the faster the time required to acquire a channel. A brute force implementation of a parallel complex correlator architecture of a signal using an input signal that is oversampled by a maximum length sequence of length 1023 and 2 × is shown in FIG. Even and odd samples correspond to 2 × oversampled data. The shift register is shifted at a rate of “clk”. The PRN generator generates a reference PRN and is shifted at a rate of clk / 2. The correlation sum for each cycle is given by the formula

Where x [n] is the complex input, gcref [k] is the PRN reference waveform, and corrsum [n] is the complex output from the correlator. FIG. 37 shows one optimization where even and odd samples share the same multiplier and adder tree.

  Implementations such as those shown above require 2046 * 2 * n input bit flip-flops for the shift register, 1023 1 × n input multipliers, and an adder summing 1023 products. As an example, if the input bit width is 2 bit samples, 1023 1 × 2 multipliers are required and 1023 of these multiplications must be summed in one clock cycle. This can be a cumbersome implementation in terms of hardware area, timing, and power. Specifically, in the FPGA implementation, the brute force implementation of the multiplier and adder structure may not be feasible given the limited resources.

  One embodiment includes a novel approach to this implementation that takes advantage of the structure available within the state of the art FPGA. Modern FPGAs include multiple configurable logic blocks (CLBs) that implement logic elements and storage elements. The look-up table that forms an essential part of the CLB can be reprogrammed as a shift register with serial shift-in but with parallel random access to storage elements. This embodiment can also be used in ASIC implementations as an efficient way to calculate correlations and as a simple transplant path from FPGA (used for prototyping) to ASIC (for high volume production). .

  Moving to the shift register implementation, certain FPGAs have shift register primitives that are mapped to CLBs. Some FPGAs have 16-bit shift registers, and some FPGAs have 32-bit shift register mapping. FIG. 41 shows a 32-bit shift register implementation derived from two 16-bit shift register primitives with parallel random access read capabilities. In this example implementation, 16-bit shift register group primitives are used to build a 32-bit shift register. Thirty-two such 32-bit shift registers are arranged in series to form a 1024-bit shift register. As shown in FIG. 42, the shift operation occurs at the “clk” rate, and the read operation occurs at 32 times the clock rate.

The adder tree can be complicated to implement a 1023 × n bit adder. For a specific FPGA, a 48-bit DSP slice that can be used as a 1023 × n-bit sequential adder can be used. The hardware structure of this embodiment is shown in FIG. The 32 values from the 32 groups of shift registers are divided into 4 groups of 8 additions. In this example, a 2-bit input is used. Each 8-number adder produces a 10-bit output that is aligned within a 12-bit group within the 48-bit adder. There is room for total increase. After 32 cycles, a 1024-bit total is obtained by adding four groups of 12-bit adders to a single 14-bit total.
Encryption and Security Within the system of an embodiment, overhead information can be encrypted using an encryption algorithm. This allows the user to use the system, be charged for the use of the system, and provide a means to control information security. A key can be applied to decrypt the signal. The key can be obtained using a PC, wireless network, hardware dongle, or can be burned into the non-volatile memory of the device in a way that the key is inaccessible by any unintended source.

  One embodiment of encryption provides both data security and authentication. The main components that are protected using encryption are transmitter, receiver, and server communications. Transmitter authentication involves unambiguously identifying a transmitter so that a malicious transmitter can be rejected. Receiver authentication is such that only authentic receivers can use the transmitted information. Receiver authorization is such that only authorized receivers (authentic receivers) are allowed to operate. Server communications are encrypted such that communications between the receiver and server and communications between the transmitter and server are protected. User data protection is also encrypted because the location tracking user database requires protection from unauthorized access.

  The encryption method of one embodiment can be roughly classified into two types: symmetric key cryptography and asymmetric key cryptography. Symmetric key encryption provides both authentication and encryption, while asymmetric key encryption provides authentication of the private key owner because the public key can be used by anyone. Symmetric key encryption of data is an order of magnitude faster than a given similar resource. 3DES and AES are examples of symmetric key cryptography. The combination of both methods is used as part of the encryption architecture of one embodiment.

  An over-the-air (OTA) broadcast message may include a general broadcast message or a system message. A typical broadcast message contains data specific to each transmitter, such as location information, transmitter timing counts, and other relevant information that helps the receiver determine its location. System messages are used to construct encryption keys, enable / disable receivers, or exchange one-way private information targeted to a specific set of receivers.

  The general format of a message in one embodiment includes a message type (parity / ECC protection), an encrypted message, and an encrypted message ECC. The ECC of the encrypted message is calculated after the message is encrypted.

  OTA broadcasts contain frames that are transmitted periodically, perhaps every second. Depending on the channel data rate, the message can be divided (segmented) across multiple frames. Each frame includes a frame type and frame data. Frame type (parity protected) indicates whether this is the first frame of a message or whether it is a continuous frame, and can also indicate a low-level format frame that can be used for other purposes . Frame data is essentially a segmented message or a low-level data frame.

  Depending on the system message type, the OTA system message can be encrypted with either the session key or the sender's private key. OTA generic broadcast messages are encrypted using a symmetric key algorithm with a session key negotiated by both the transmitter and receiver, as described herein. This provides mutual authentication, i.e., the transmitter can be authenticated by the receiver, and only the authenticated receiver can decrypt the OTA broadcast. Session keys are known to all transmitters and receivers and are changed periodically. The key change message is encrypted using the past 2-3 session keys, allowing a receiver that has not been active for a period of time to synchronize with the current session key.

  OTA broadcasts also include periodic system messages that are encrypted with the sender's private key. The receiver can unambiguously identify the authenticity of the transmitter by using the associated public key. If the session key is compromised, this mechanism ensures that unauthorized transmitters cannot be implemented.

  FIG. 44 is a block diagram of session key setup, under an embodiment. Each receiver comprises a unique device ID and a device specific key. FIG. 45 is a flow diagram for encryption, under an embodiment. The WAPS system data server maintains a device ID / device unique key pairing database. Receiver initialization between the receiver and the WAPS data server is facilitated using a data connection specific to the receiver type (eg GPRS / USB / modem). This connection is encrypted using the device unique key after the device identifies itself by the device ID. During this initialization, the current session key, transmitter public key, and licensing period (ie, the duration for which the receiver is authorized) are exchanged. Receiver initialization may be performed when the receiver loses the current session key (initial power-up) or when the session key is out of sync (extended power-off). The session key is updated periodically and the new key used for the update is encrypted using the previous N keys.

  The OTA data rate may be inadequate to be the only mechanism for authenticating the receiver. However, the system message protocol of one embodiment supports device ID specific and device ID distance based receiver authentication.

  A compromised session key requires that all receivers be re-initialized. Therefore, the session key storage must be prevented from being tampered with in the device. Session keys that are stored outside the device's cryptographic boundary (ie, any type of attached storage) are encrypted using the device's protected key.

  Since the sender periodically sends authentication information using its private key, the compromised session key cannot be used to impersonate the sender. Therefore, the sender's private key must never be compromised.

  In an alternative embodiment shown in FIG. 46, the key can be delivered directly to the receiver via a communication link from the WAPS server, or routed via a third party application or service provider. Can do. The key can have a certain validity period. Keys can be made available on a per application basis or on a per device basis based on contractual agreements with customers. Each time a location request is made by either an application on the receiver or an application on the network, the key is checked for validity before retrieving the parameters for calculating the location or position from the WAPS engine. The exchange of keys and information to the WAPS server can occur using proprietary protocols or via standard protocols such as OMA SUPL.

  The security architecture of the system can be implemented as a combination of the architectures shown in FIGS.

  A parameter sensor can be integrated into the receiver of the WAPS system for time tagging the measurements from the sensor and / or for location tagging. Parameter sensors can include, but are not limited to, temperature sensors, humidity sensors, weight sensors, and scanner type sensors, to name a few examples. For example, an X-ray detector can be used to determine whether a tracked receiver or a device that includes the tracked receiver passes through the X-ray equipment. The time of the x-ray event and the location of the x-ray equipment can be tagged by the detector. In addition, other parameter sensors can be integrated into the WAPS system to both time tag and location tag the measurements from the sensors.

  Users can be billed for the system on an hourly, daily, weekly, monthly, and yearly basis on an hourly, daily, weekly, monthly, and yearly basis for individuals or assets, for each application on the device.

  The location and height of the receiver unit can be sent to any application or network server on the terminal using a communication protocol. Alternatively, the raw distance measurement can be sent to the network via a communication protocol. The communication protocol can be a standard serial interface or other digital interface to an application on the terminal or to a server via a standard or proprietary wireless protocol. A possible way to couple or connect to a server via a standard protocol is to use SMS messaging to another phone connected to the server or, alternatively, a wireless data service to a web server. including. The transmitted information includes one or more of latitude / longitude, height (if available), and time stamp. An application on the server or terminal unit can initiate the position determination. The user's location can be communicated directly from the server or by an application on the server.

A WAPS stand-alone system independent of the GPS receiver can be used to determine the location of the device. A WAPS system alone or an integrated WAPS and GPS and / or other positioning system can be implemented to coexist on a media card with a media storage card (such as an SD card). Implement a WAPS system alone or an integrated WAPS and GPS system and / or other positioning systems to coexist on a cellular telephone Subscriber Identity Module (SIM) card to enable tracking of the SIM card be able to.
Accurate positioning using carrier phase One way to enhance WAPS system performance to further improve accuracy (up to 1 m) is to implement a carrier phase positioning system as described below. The beacon is set up as a normal WAPS transmitter. For this method, it may be desirable (but not essential) not to use TDMA slotting to facilitate simple continuous phase tracking. When TDMA is not used, the near-far problem can be overcome through interference cancellation at the receiver and increased dynamic range. A WAPS receiver that supports such a method can measure and timestamp the code phase and carrier phase in a continuous manner for all visible satellites. In addition, there is a reference receiver at a known investigated location that can also make similar measurements of code and carrier phase in a continuous manner. Measurements from the WAPS receiver and the reference receiver can be combined to calculate the location at either the device or the server. The configuration of such a system is the same as the differential WAPS system.

  The carrier phase measurement is more accurate than the code phase measurement, but includes an unknown integer number of carrier phase cycles, called integer ambiguity. However, there is a form of finding integer ambiguity called ambiguity resolution. Here, for improved accuracy, we consider one method of using measurements in multiple epochs, using an extension of the local minimum search algorithm to iteratively solve for user receiver positions.

  Consider first the carrier phase measurement at the user receiver at the next single epoch.

Where φ, λ, f, and N are the carrier phase, wavelength, frequency, and integer cycle, respectively, dt is the clock bias, r is the distance, and ε is the measurement error, The subscript u represents the user receiver, and k represents the transmitter number.

The distance is relative to user position p _u and transmitter position p ^(k)

As given.

  To eliminate errors in transmitter clock bias knowledge, the corresponding carrier phase equation

, Consider another receiver at a known location (referred to as the reference receiver). Here, the subscript r represents the reference receiver, and (2) is subtracted from (1).

And this is

Where (·) _ur = (·) _u − (·) _r .

Since dt _u r is not of interest, we remove this by calculating the difference in (5) for different values of index (k), so-called double difference observable equation

Where

It is.

  Next, equation (6) becomes

As

At unknown user position p _u , where
^{(8) γ (kl) =} ‖p r -p (k) ||-‖p _r -p ^(l) ||
It is.

  Usually, the transmitter l used for the double difference calculation is one of the transmitters and for convenience it is labeled as l

Or (10) φ = λ ⁻¹ · f (p _u ) + N + ε
Leads to an expression in the form of a matrix.

Equation (10) is a nonlinear equation at an unknown user position _pu .
The local minimum search algorithm works with linear equations, so equation (10) is linearized and solved iteratively as follows: In an iterative m, approximation to the _{p u} is

And here

And

And where
(13)

Where l ^(k) is the line of sight line vector

It is.

Next, Formula (10) is (13) y = G · x · + N + ε
However,

,

And is x = Δp _u.

Equation (13) is linear with x = Δp _u and is solved for Δp _u using the local minimum search algorithm given below. Using Δp _u so obtained, equation (11) is used to obtain p _u at iteration m, and then p _u so obtained is the next iteration At (m + 1)

Used as. The iteration is continued until Δp _u is small enough to determine convergence. At the beginning of the iteration,

Can be obtained from the code phase based solution.

  Now consider solving equation (13).

Be the covariance matrix of the double difference carrier phase error vector. This is obtained as follows. Single differential observable

The error variance at

And where

and

Is the respective carrier phase error variance that is assumed to be independent of transmitter k.

The variance of

And j ≠ k

When

The mutual variance between

This is a common term

Is the dispersion of. Therefore,

It is.

The weighted least squares solution of (13) is
(15)

Where ^GL is the left inverse matrix of G,

It is.

  The residual vector is

This is a function of N, and the local minimum search is

Try to minimize the weighted norm square of the residual with respect to N. To solve (17), under the constraint that N is an integer,

Please consider solving. Since W is idempotent (W ^T = W and W · W = W),

And

It is. Therefore, the search for N is limited to N that satisfies (18).

After solving for N, the estimated value of x = Delta] p _u is obtained from equation (15). The matrices G and ^GL of dimensions (n−1) × 3 and 3 × (n−1) respectively are (n−1)> 3, so that the (n−1) × (n−1) matrix S and Since W is less than 3 from the maximum rank (n−1), each has 3 ranks.

  Using the QR decomposition of W in equation (18) (LU decomposition can also be used)

And where

Is an orthonormal matrix

, R is an upper triangular matrix and the result

And

It is.

  Therefore,

Can be obtained by searching for N ₂ in a three-dimensional box with integer values, obtaining N1 from (21), and choosing N that minimizes c (N) in (17). Search N ₂ is centered on the value of N ₂ from the previous iteration. In the 0th iteration,

N ₂ , the part behind N obtained as a fractional part of

Is a code phase based solution. The size of the 3D search box depends on the uncertainty of the code phase based solution. This box can be divided into smaller sub-boxes, and the center of each smaller sub-box is

You can try as

  The above method used a single epoch of measurements to determine position. In the description below, an extension to the single epoch method is described. Multiple epoch measurements are measured close enough in time, where user receiver movement is negligible. Furthermore, the integer ambiguity of the initial epoch remains the same in the subsequent epoch so that no new unknown integer ambiguity is introduced in the subsequent epoch. Multiple epoch measurements do not give independent equations because the transmitter location is fixed (unlike GNSS, where satellite transmitter movement changes the line of sight and thus gives an independent equation) . Thus, multiple epoch measurements do not help in solving integer ambiguity as floating point ambiguity (the number of independent expressions is greater than the total number of unknown ambiguities and three position coordinates. Different from the case). However, multiple epoch measurements allow for more carrier phase measurement error and still allow for successful ambiguity resolution. In the case of multiple epochs, equation (13) is

become. According to the expansion for the single epoch case like the above equation, the problem is

Reduced to the problem of finding N, where

It is. Next, to solve (23) for N,
(24)

However,

The

Consider solving according to the equations (19) to (21) above using a QR decomposition of (which can also use LU decomposition). Again, after being solved for N, the estimated value of x = Delta] p _u is obtained from equation (15). When the estimated value of the x = Delta] p _u is small, repeated in formula (11) is stopped in order to obtain the user location p _u. Usually, if each component of x is less than 1e-6 in magnitude, convergence is declared and the iteration is stopped.

The next step is to verify whether the converged user position p _u is correct. This is performed based on the residual obtained from (10) as mod (φ−λ− ¹ · f (p _u ) −N, λ). The maximum absolute value of each epoch residual is

If less than, the converged solution is accepted as a solution, otherwise the search is continued by selecting a new sub-box. Usually, the scale factor κ in the verification test can be selected to be 5. After the solution has been verified, the differential WAPS system described above can achieve accuracy close to or better than 1 m.

  This differential WAPS carrier phase system can be overlaid on top of a conventional WAPS system through the addition of a reference receiver, or it can be standalone. The differential WAPS carrier phase system can be used to deliver highly accurate positioning in certain localized target areas (mall, warehouse, etc.).

  In a W-CDMA system, two receive chains are used to improve receive diversity. When WAPS coexists with W-CDMA, one of the receive chains can be temporarily used for receiving and processing the WAPS signal. In some cases of W-CDMA and CDMA architectures, the entire receive chain is tuned by tuning the receiver to the WAPS band and temporarily processing the WAPS signal while temporarily deferring the processing of the W-CDMA / CDMA signal. , Can be reused to receive W-WAPS signals. In certain other embodiments in which the GSM receive chain is multiplexed with the W-CDMA receive chain, the receiver can be further time-shared for use with WAPS reception.

  In order to save power after it is determined which signal from which tower is used for position determination in the WAPS system or any other TDMA system, most of the receivers of one embodiment detect the signal Is switched off during a slot that is either not and / or the signal from the tower radiating into the slot is not used for position determination. In the case of detection of movement, position change, or signal condition change, the receiver of one embodiment turns on for all slots to determine which slots can be used for the next set of position calculations. Can be switched.

  Embodiments described herein include a positioning system that includes a ground transmitter network that includes a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. The system includes a reference sensor array that includes at least one reference sensor unit positioned at a known location. The system includes a remote receiver that includes an atmospheric sensor that collects atmospheric data at the location of the remote receiver. The system includes a positioning application that runs on a processor and is coupled to a remote receiver. The positioning application includes atmospheric data, reference data from a set of reference sensor units in a reference sensor array, and information derived from at least one of a positioning signal and a satellite signal that is a signal of a satellite-based positioning system. Use to calculate the position of the remote receiver. The position includes the elevation.

  An embodiment described herein is a positioning system, a terrestrial transmitter network including a plurality of transmitters that broadcast positioning signals including at least ranging signals and positioning system information, wherein the ranging signals are A ground transmitter network that includes information used to measure the distance to the transmitter that broadcasts the ranging signal, and a reference sensor array that includes at least one reference sensor unit positioned at a known location; A remote receiver that includes an atmospheric sensor that collects atmospheric data at the location of the remote receiver and a positioning application that runs on the processor and is coupled to the remote receiver, wherein the positioning application includes atmospheric data and a reference sensor Reference data from a set of reference sensor units in the array and positioning signals And a position of the remote receiver using information derived from at least one of the satellite signals that are signals of the satellite-based positioning system, and the position includes a positioning application, including elevation Includes system.

  Embodiments described herein include a positioning system that includes a ground transmitter network that includes a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. The system includes a reference sensor array that includes at least one reference sensor unit positioned at a known location. The system includes a remote receiver that includes an atmospheric sensor that collects atmospheric data at the location of the remote receiver. The system includes a positioning application that runs on a processor and is coupled to a remote receiver. The positioning application uses atmospheric data and reference data from a set of reference sensor units in the reference sensor array to generate a reference pressure estimate at the location of the remote receiver. The positioning application uses the reference pressure estimate and information derived from at least one of the positioning signal and a satellite signal that is a signal of a satellite-based positioning system to calculate the position of the remote receiver. The position includes the elevation.

  An embodiment described herein is a positioning system, a terrestrial transmitter network including a plurality of transmitters that broadcast positioning signals including at least ranging signals and positioning system information, wherein the ranging signals are A ground transmitter network that includes information used to measure the distance to the transmitter that broadcasts the ranging signal, and a reference sensor array that includes at least one reference sensor unit positioned at a known location; A remote receiver that includes an atmospheric sensor that collects atmospheric data at the location of the remote receiver and a positioning application that runs on the processor and is coupled to the remote receiver, the positioning application including an atmospheric data and reference sensor array Using reference data from a set of reference sensor units Generating a reference pressure estimate at the position of the receiver, and the positioning application provides information derived from at least one of the reference pressure estimate and a satellite signal that is a signal of a positioning signal and a satellite-based positioning system. Are used to calculate the position of the remote receiver, the position including a positioning system including a positioning application, including elevation.

  The positioning application of one embodiment is hosted on a remote receiver, which calculates the location.

  The remote receiver of one embodiment operates in a powered down state when the positioning signal is at least one of undetected and unusable.

  The remote receiver of an embodiment uses a set of positioning signals from a plurality of sets of transmitters to determine a position, and the remote receiver has at least one of the set of positioning signals not detected and unusable. When it is one, it operates with power reduced.

  In one embodiment, the remote receiver is in a state of being powered down in response to detecting at least one of a remote receiver movement, a change in the position of the remote receiver, and a change in the signal condition of the positioning signal. Transition to full power state.

  The system of an embodiment includes a server coupled to a remote receiver, the positioning application is hosted on the server, and the server calculates the location.

  The system of an embodiment includes a server coupled to the remote receiver, and the positioning application is distributed between the remote receiver and the server.

  The first mode of operation of the remote receiver of one embodiment includes terminal-based positioning where the remote receiver calculates the position.

  The second mode of operation of the remote receiver of one embodiment includes network-based positioning where the server calculates the location.

  The known location of one embodiment is the location of a transmitter set of multiple transmitters.

  The positioning application of one embodiment includes a pressure surface gradient model that uses reference data from a set of reference sensor units to generate an equivalent reference elevation pressure at the location of the remote receiver.

  The positioning application of one embodiment uses the equivalent reference elevation pressure as a reference value for generating elevation.

  The positioning application of one embodiment uses the reference data from each reference sensor unit to generate an equivalent reference elevation pressure for each reference sensor unit in the set of reference sensor units.

  The reference data of one embodiment includes pressure data, temperature data, and location data for each reference sensor unit in the set of reference sensor units, and the location data includes elevation.

  The positioning application of one embodiment uses the equivalent reference elevation pressure of each reference sensor unit of the set of reference sensor units and the latitude and longitude of the remote receiver to generate an equivalent reference elevation pressure at the location of the remote receiver. .

  The positioning application of one embodiment uses the atmospheric data and the equivalent standard elevation pressure at the remote receiver location to generate the elevation of the remote receiver.

  In one embodiment, at least one reference sensor unit is co-located with at least one transmitter of the plurality of transmitters.

  The at least one reference sensor unit of an embodiment includes a plurality of reference sensor units, the first set of the plurality of reference sensor units being disposed at the same position as the first set of the plurality of transmitters. The second set of units is located at a location different from the locations of the plurality of transmitters.

  The at least one reference sensor unit of an embodiment is at a location that is different from the location of the plurality of transmitters.

  The atmospheric sensor of one embodiment collects pressure and temperature data at the location of the remote receiver.

  The atmospheric sensor of one embodiment determines pressure data with a resolution in the range of less than about 36 Pascals.

  The remote receiver of one embodiment detects the rate of change of pressure data.

  The positioning application of one embodiment uses the rate of change to determine the vertical speed of the remote receiver.

  The temperature data of one embodiment includes the ambient temperature at the location of the remote receiver, and the atmospheric sensor determines the temperature data with a resolution of at least one equal to and less than about 3 degrees Celsius.

  Each reference sensor unit of an embodiment includes at least one atmospheric reference sensor that collects reference pressure data and reference temperature data at known locations of the atmospheric reference unit.

  The at least one atmospheric reference sensor of one embodiment determines the reference pressure data with a resolution in the range of about 2-36 Pascals.

  The reference temperature data of one embodiment includes the ambient temperature at a known location, and the atmospheric reference sensor determines the temperature data with a resolution of at least one equal to and less than about 3 degrees Celsius.

  The atmospheric reference sensor of one embodiment is calibrated for a limited temperature range, and the limited temperature range is determined based on the temperature to which the atmospheric reference sensor is exposed.

  Each atmospheric reference sensor in one embodiment continuously collects reference pressure data and reference temperature data at a known location.

  The atmospheric reference sensor of one embodiment is positioned to collect a reference pressure and a reference temperature in relatively stationary air.

  The atmospheric reference sensor of one embodiment filters reference pressure data and reference temperature data.

  The atmospheric reference sensor of one embodiment filters the reference pressure data and the reference temperature data using an adaptive time scale.

  Each reference sensor unit of one embodiment includes a wind detector that determines wind data, the wind data including the direction and intensity of the local wind.

  The positioning application of one embodiment uses wind data to perform at least one of correction and filtering of variations in the atmospheric sensor.

  The at least one reference sensor unit of an embodiment includes a plurality of atmospheric reference sensors.

  The system of one embodiment includes a communication link coupled between a reference sensor array and a remote receiver.

  The reference sensor array of one embodiment broadcasts atmospheric reference data.

  The reference sensor array of one embodiment broadcasts raw data of atmospheric reference data.

  The reference sensor array of one embodiment broadcasts difference data of reference data.

  The difference data of one embodiment is derived relative to at least one constant value.

  The differential data of one embodiment includes differential pressure data derived as standard atmospheric offset values.

  The remote receiver of one embodiment receives the reference data via broadcast.

  The reference sensor array of one embodiment broadcasts reference data multiple times per second.

  The reference sensor array of one embodiment broadcasts reference data multiple times per measurement.

  The remote receiver of one embodiment determines a set of atmospheric reference sensors to be queried and pulls reference data from the set of atmospheric reference sensors via a communication link.

  The positioning application of one embodiment processes the reference data and determines an equivalent reference elevation pressure for each reference sensor unit in the set of reference sensor units.

  The reference data of one embodiment includes the location of each atmospheric reference unit.

  The location of one embodiment includes latitude and longitude.

  The location of one embodiment includes a height.

  The reference data of one embodiment includes the measured outside temperature from each air reference unit.

  The reference data of one embodiment includes a confidence measure.

  Each reference sensor unit of one embodiment processes the reference data of the reference sensor unit to determine the equivalent reference altitude pressure of the reference sensor unit.

  The reference data of one embodiment includes the location of each atmospheric reference sensor.

  The location of one embodiment includes latitude and longitude.

  The location of one embodiment includes a height.

  The reference data of one embodiment includes an equivalent reference elevation pressure.

  The reference data of one embodiment includes a confidence measure.

  The elevation of one embodiment includes an estimated elevation of each floor within the at least one structure.

  The system of an embodiment includes a database coupled to a plurality of remote receivers including remote receivers, the database including estimated elevations received from the plurality of remote receivers.

  The system of an embodiment includes a learning application coupled to the server, which processes the estimated elevations of the plurality of remote receivers and revises the database using the estimated elevations.

  The at least one reference sensor unit of an embodiment includes at least one local reference sensor unit local to at least one of location and structure.

  The reference data of one embodiment includes data of at least one local reference sensor unit.

  The system of an embodiment includes automatically calibrating the remote receiver's atmospheric sensor using reference data aggregated over a specified time period.

  The system of an embodiment generates aggregated reference data by identifying when the remote receiver is at a known location, and accumulates deviations in the atmospheric data corresponding to the known location; Generating a corrected calibration from the accumulated deviation.

  The system of one embodiment includes automatically calibrating the remote receiver's atmospheric sensor when the elevation pressure and atmospheric pressure at the remote receiver's location are known.

  The location of the remote receiver in one embodiment is determined using satellite signals.

  The system of an embodiment includes determining an elevation using a reference elevation.

  The reference elevation in one embodiment minimizes the elevation difference between elevations calculated using at least one of atmospheric data and reference data.

  The reference elevation in one embodiment includes the average elevation of the atmospheric reference unit.

  The reference elevation in one embodiment includes the average elevation of the area where the remote receiver is located.

  The elevation of one embodiment includes an estimated elevation derived using local constraint data.

  The local constraint data in one embodiment includes terrain data for terrain near the location of the remote receiver.

  The local constraint data in one embodiment includes the height of at least one structure near the location of the remote receiver.

  The local constraint data in one embodiment includes the elevation of at least one other remote receiver near the location of the remote receiver.

  The positioning application of one embodiment determines the altitude using atmospheric data, reference data, and local constraint data.

  The system of an embodiment includes a database coupled to a positioning application, the database including historical data measured during a time period, wherein the historical data includes reference data for a reference sensor array and air for a plurality of remote receivers. Contains data.

  The positioning application of one embodiment determines the elevation using historical data.

  The system of an embodiment includes optimizing at least one reference sensor unit of the reference sensor array using historical data.

  The system of an embodiment includes determining elevation by relaxing a constant equivalent reference elevation pressure assumption between the reference location of the reference sensor unit and the current location of the remote receiver.

  The system of an embodiment includes converting a first equivalent reference elevation pressure at a reference location to a second equivalent reference elevation pressure at a standard temperature. The system of an embodiment includes determining a local temperature at the current location and using the local temperature to convert the second equivalent reference elevation pressure to a third equivalent reference elevation pressure. The system of an embodiment includes determining a current location elevation using a third equivalent reference elevation pressure.

  The system of one embodiment includes using the reference data at each reference sensor unit of the set of reference sensor units to determine the variation in equivalent reference elevation pressure with horizontal location. The system of an embodiment includes determining the best estimate of the reference elevation pressure at the current location by combining the equivalent reference elevation pressures of the set of reference sensor units.

  Determining the best estimate of equivalent reference elevation pressure in one embodiment includes using a weighted average technique, where the weight is a function of the horizontal distance between the location of the reference sensor unit and the current position. .

  Determining the best estimate of equivalent reference altitude pressure in one embodiment is the least squares to create a secondary surface that best fits the calculated sea level pressure at each reference sensor unit of the set of reference sensor units. Using fitting and interpolating the best estimate of equivalent reference elevation pressure at the current location using the nth order surface.

  The system of an embodiment includes converting a first equivalent reference elevation pressure at each reference sensor unit of the set of reference sensor units into a second equivalent reference elevation pressure at a standard temperature. The system of one embodiment includes determining the best estimate of the equivalent reference elevation pressure at the current location by combining the second equivalent reference elevation pressures from each reference unit.

  Determining the best estimate of equivalent reference elevation pressure in one embodiment includes using a weighted average technique, where the weight is a function of the horizontal distance between the location of the reference sensor unit and the current position. .

  Determining the best estimate of the equivalent reference elevation pressure of one embodiment is to create a secondary surface that best fits the calculated equivalent reference elevation pressure at each reference sensor unit of the set of reference sensor units. Using a least squares fit and interpolating the best estimate of sea level pressure at the current location using the nth order surface.

  The remote receiver of one embodiment includes a high speed clock.

  The remote receiver of one embodiment receives pulse edges from a common time reference, and the remote receiver uses a high speed clock to determine the time difference between the occurrence of the pulse edge and the rising edge of the sample clock .

  The remote receiver of one embodiment applies a correction to the estimated distance based on the time difference, and the correction improves the accuracy of the estimated distance.

  The remote receiver of one embodiment includes a correlator that correlates the received signal with a pseudo-random code, the correlator comprising a first shift register including a plurality of serial sets of second shift registers having parallel random access read capability. Including.

  Each set of the plurality of sets of second shift registers of an embodiment includes a plurality of serial shift register group primitives.

  Each shift register group primitive in one embodiment includes an n-bit shift register group primitive.

  Each shift register group primitive in one embodiment includes a 16-bit shift register group primitive.

  Each set of second shift registers in one embodiment forms a 32-bit shift register.

  The serial multiple sets of second shift registers in one embodiment include multiple sets of n-bit shift registers.

  The series set of second shift registers in one embodiment includes 32 sets of second shift registers, and the first shift register is a 1024 bit shift register.

  The shift operation of the first shift register of one embodiment occurs at the clock rate of the clock coupled to the correlator.

  The read operation of the first shift register of one embodiment occurs at a rate that is at least twice the clock rate.

  The read operation of the first shift register of one embodiment occurs at 32 times the clock rate.

  The system of an embodiment includes a series of adders coupled to the output of the series of sets of second shift registers.

  The serial multiple adders of one embodiment include an adder tree, which includes a wider bit-width adder primitive.

  The serial multiple adders of one embodiment include an adder coupled to each set of multiple sets of n-bit shift registers.

  The series of adders of an embodiment includes a first adder coupled to the output of the first plurality of sets of second shift registers and a first adder coupled to the output of the second plurality of sets of second shift registers. A second adder, a third adder coupled to the output of the third plurality of sets of the second shift register, and a fourth adder coupled to the output of the fourth plurality of sets of the second shift register. .

  The system of one embodiment includes a terminating adder coupled to the output of a plurality of adders in series.

  The system of an embodiment includes aligning the outputs of the series adders in the series groups in the termination adder.

  The output of the first adder of one embodiment is aligned within the first group, the output of the second adder is aligned within the second group, and the output of the third adder is within the third group. And the output of the fourth adder is aligned in the fourth group in the terminal adder.

  The termination adder of one embodiment forms a sum by adding the contents of multiple groups in series.

  The remote receiver of an embodiment temporarily uses one native receive chain of the remote receiver's multiple native receive chains to acquire at least one of the positioning signal and the satellite signal.

  The multiple native receive chains of one embodiment include diversity receive chains that improve receive diversity.

  The remote receiver of one embodiment includes a wideband receiver.

  The remote receiver of one embodiment includes a broadband cellular band receiver.

  The remote receiver of one embodiment uses a diversity receive chain to acquire a positioning signal at least one of temporary and permanent.

  104. The positioning system of claim 2, comprising a communication system coupled to at least one of the remote receiver and the plurality of transmitters, wherein the communication system is a cellular communication system.

  The transmitters of one embodiment are synchronized, and each transmitter of the transmitters transmits a signal that includes a pseudo-random sequence and assistance data.

  Assistance data in one embodiment includes system time at the rising edge of a waveform pulse, system time at the falling edge of a waveform pulse, geocode data for multiple transmitters, and adjacent adjacent to multiple transmitters. Of transmitter geocode data, index of sequence used by at least one transmitter in the vicinity of multiple transmitters, clock timing correction of at least one transmitter, local atmospheric correction, and WAPS timing relative to GNSS time. Display of relationship and local environment to help remote receiver in pseudorange resolution, offset from base index of set of pseudorandom sequences, list of pseudorandom sequences from set of transmitters, and specific pseudorandom sequences List of transmitters that use Of including at least one of the at least one.

  In one embodiment, the positioning application formulates a set of equations as a non-linear objective function and generates a best estimate of the position as a set of position parameters that minimizes the objective function, thereby allowing the remote receiver to Calculate the position.

  The positioning application of one embodiment calculates the location of the remote receiver by formulating the linearized set of equations and solving the linearized set of equations using the least squares method. .

  The positioning application of one embodiment uses the approximate location of the transmitter set of multiple transmitters and the received signal strength (RSS) data of the set of transmitters to calculate the position of the remote receiver.

  The positioning application of one embodiment stores a sample segment of a positioning signal in a remote receiver and then processes the sample segment to retrieve, obtain and calculate distances to multiple transmitters. And calculate the position of the remote receiver.

  The positioning application of one embodiment uses the received signal strength data of the remote receiver to calculate the position of the remote receiver.

  The positioning application of one embodiment calculates the position of the remote receiver using at least one of the carrier phase data and the code phase data of the positioning signal.

  The positioning application of one embodiment calculates the position of the remote receiver using differential positioning relative to at least one reference receiver.

  The positioning application of one embodiment uses at least one of a distance measurement and a distance measurement surrogate from the opportunity signal to calculate a position of the remote receiver, where the opportunity signal is a positioning system, Received from Global Navigation Satellite System (GNSS), Global Positioning System (GPS), Differential Positioning System, Radio Signal, Television Signal, Wireless Network System, WiFi System, Cellular System, and Bluetooth System.

  The positioning application of one embodiment calculates the final position of the remote receiver using distance measurements from at least one additional signal source combined with the distance measurements determined using the positioning signal. The final position includes at least one of latitude, longitude, and height.

  The positioning application of an embodiment includes a position measurement from at least one additional signal source combined with a position measurement determined using the positioning signal and a position quality metric from at least one additional signal source. And compute the optimized location solution for the remote receiver.

  The positioning application of one embodiment uses hybrid positioning to calculate the position of the remote receiver, where the hybrid positioning includes measurements from a positioning signal and measurements from at least one additional source.

  The positioning system information of one embodiment includes timing synchronization information and corresponding correction information.

  Embodiments described herein include a reference system that includes a reference sensor array that includes at least one set of reference sensor units. Each set includes at least one reference sensor unit positioned at a known location. The system includes a remote receiver that includes an atmospheric sensor that collects atmospheric data at the location of the remote receiver. The system is a positioning application that runs on a processor and is coupled to a remote receiver, the positioning application using atmospheric data and reference data from at least one set of reference sensor units of a reference sensor array. Includes a positioning application that generates a reference pressure estimate at the location of the remote receiver. The positioning application uses the reference pressure estimate to calculate the elevation of the remote receiver.

  Embodiments described herein are reference sensor arrays that include at least one set of reference sensor units, each set including at least one reference sensor unit positioned at a known location. A remote receiver that includes an array and an atmospheric sensor that collects atmospheric data at the location of the remote receiver, and a positioning application that runs on the processor and is coupled to the remote receiver, wherein the positioning application includes atmospheric data and reference Reference data from at least one set of reference sensor units in the sensor array is used to generate a reference pressure estimate at the location of the remote receiver, and the positioning application uses the reference pressure estimate to A reference system, including a positioning application, No.

  Embodiments described herein include a positioning system that includes a ground transmitter network that includes a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. The system includes a remote receiver that acquires at least one of a positioning signal and a satellite signal. The satellite signal is a signal of a satellite-based positioning system. The first mode of operation of the remote receiver includes terminal-based positioning where the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal. The remote receiver includes a correlator that correlates the received signal with a pseudo-random code and a server coupled to the remote receiver. The second mode of operation of the remote receiver includes network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signal and the satellite signal. The remote receiver receives at least one of the positioning signal and the satellite signal and transfers information derived therefrom to the server.

  Embodiments described herein are terrestrial transmitter networks that include a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information, wherein the ranging signals broadcast ranging signals. A terrestrial transmitter network including information used to measure the distance to the transmitter to be transmitted and a remote receiver for obtaining at least one of a positioning signal and a satellite signal, wherein the satellite signal is a satellite A base positioning system signal, wherein the first mode of operation of the remote receiver includes terminal based positioning in which the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal; The remote receiver is coupled to the remote receiver and the remote receiver, including a correlator that correlates the received signal with a pseudo-random code The second mode of operation of the remote receiver includes a network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signal and the satellite signal. The remote receiver includes a positioning system including a server that receives at least one of a positioning signal and a satellite signal and forwards information derived therefrom to the server.

  The correlator of one embodiment includes a first shift register including a plurality of serial sets of second shift registers having parallel random read capabilities.

  Each set of the plurality of sets of second shift registers of an embodiment includes a plurality of serial shift register group primitives.

  Each shift register group primitive in one embodiment includes an n-bit shift register group primitive.

  Each shift register group primitive in one embodiment includes a 16-bit shift register group primitive.

  Each set of second shift registers in one embodiment forms a 32-bit shift register.

  The serial multiple sets of second shift registers in one embodiment include multiple sets of n-bit shift registers.

  The series set of second shift registers in one embodiment includes 32 sets of second shift registers, and the first shift register is a 1024 bit shift register.

  The shift operation of the first shift register of one embodiment occurs at the clock rate of the clock coupled to the correlator.

  The read operation of the first shift register of one embodiment occurs at a rate that is at least twice the clock rate.

  The read operation of the first shift register of one embodiment occurs at 32 times the clock rate.

  The system of an embodiment includes a series of adders coupled to the output of the series of sets of second shift registers.

  The serial multiple adders of one embodiment include an adder tree, which includes a wider bit-width adder primitive.

  The serial multiple adders of one embodiment include an adder coupled to each set of multiple sets of n-bit shift registers.

  The series of adders of an embodiment includes a first adder coupled to the output of the first plurality of sets of second shift registers and a first adder coupled to the output of the second plurality of sets of second shift registers. A second adder, a third adder coupled to the output of the third plurality of sets of the second shift register, and a fourth adder coupled to the output of the fourth plurality of sets of the second shift register. .

  The system of one embodiment includes a terminating adder coupled to the output of a plurality of adders in series.

  The system of an embodiment includes aligning the outputs of the series adders in the series groups in the termination adder.

  The output of the first adder of one embodiment is aligned within the first group, the output of the second adder is aligned within the second group, and the output of the third adder is within the third group. And the output of the fourth adder is aligned in the fourth group in the terminal adder.

  The termination adder of one embodiment forms a sum by adding the contents of multiple groups in series.

  Embodiments described herein include a positioning system that includes a ground transmitter network that includes a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. The system includes a remote receiver that acquires at least one of a positioning signal and a satellite signal. The satellite signal is a signal of a satellite-based positioning system. The first mode of operation of the remote receiver includes terminal-based positioning where the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal. The remote receiver operates with power reduced when no positioning signal is detected. The system includes a server coupled to a remote receiver. The second mode of operation of the remote receiver includes network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signal and the satellite signal. The remote receiver receives at least one of the positioning signal and the satellite signal and transfers information derived therefrom to the server.

  Embodiments described herein are terrestrial transmitter networks that include a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information, wherein the ranging signals broadcast ranging signals. A terrestrial transmitter network and a remote receiver that acquires at least one of a positioning signal and a satellite signal, including information used to measure a distance to the transmitter, wherein the satellite signal is a satellite A base positioning system signal, wherein the first mode of operation of the remote receiver includes terminal based positioning in which the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal; The remote receiver operates with the power reduced when no positioning signal is detected, and the remote receiver A combined server, wherein the second mode of operation of the remote receiver is a network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signal and the satellite signal. The remote receiver includes a positioning system including a server that receives at least one of a positioning signal and a satellite signal and forwards information derived therefrom to the server.

  The positioning application of one embodiment is hosted on a remote receiver, which calculates the location.

  The remote receiver of one embodiment operates in a powered down state when the positioning signal is at least one of undetected and unusable.

  The remote receiver of an embodiment uses a set of positioning signals from a plurality of sets of transmitters to determine a position, and the remote receiver has at least one of the set of positioning signals not detected and unusable. When it is one, it operates with power reduced.

  In one embodiment, the remote receiver is in a state of being powered down in response to detecting at least one of a remote receiver movement, a change in the position of the remote receiver, and a change in the signal condition of the positioning signal. Transition to full power state.

  Embodiments described herein include a positioning system that includes a ground transmitter network that includes a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. The system includes a remote receiver that acquires at least one of a positioning signal and a satellite signal. The satellite signal is a signal of a satellite-based positioning system. The first mode of operation of the remote receiver includes terminal-based positioning where the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal. The remote receiver includes a high speed clock. The system includes a server coupled to a remote receiver. The second mode of operation of the remote receiver includes network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signal and the satellite signal. The remote receiver receives at least one of the positioning signal and the satellite signal and transfers information derived therefrom to the server.

  Embodiments described herein are terrestrial transmitter networks that include a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information, wherein the ranging signals broadcast ranging signals. A terrestrial transmitter network including information used to measure the distance to the transmitter to be transmitted and a remote receiver for obtaining at least one of a positioning signal and a satellite signal, wherein the satellite signal is a satellite The first operating mode of the remote receiver includes a terminal-based positioning mode in which the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal. The remote receiver is a remote receiver including a high-speed clock and a server coupled to the remote receiver, The second mode of operation of the receiver includes network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signal and the satellite signal, A positioning system including a server that receives at least one of the signal and the satellite signal and forwards information derived therefrom to the server.

  The remote receiver of one embodiment receives pulse edges from a common time reference, and the remote receiver uses a high speed clock to determine the time difference between the occurrence of the pulse edge and the rising edge of the sample clock .

  The remote receiver of one embodiment applies a correction to the estimated distance based on the time difference, and the correction improves the accuracy of the estimated distance.

  Embodiments described herein include a positioning system that includes a ground transmitter network that includes a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information. The ranging signal includes information used to measure the distance to the transmitter that broadcasts the ranging signal. The system includes a remote receiver that acquires at least one of a positioning signal and a satellite signal. The remote receiver temporarily uses one native receive chain of the remote receiver's multiple native receive chains to obtain at least one of the positioning signal and the satellite signal. The satellite signal is a signal of a satellite-based positioning system. The first mode of operation of the remote receiver includes terminal-based positioning where the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal. The system is a server coupled to a remote receiver, wherein the second mode of operation of the remote receiver is the location of the remote receiver from information derived from at least one of the positioning signal and the satellite signal by the server. Includes servers, including network-based positioning to calculate. The remote receiver receives at least one of the positioning signal and the satellite signal and transfers information derived therefrom to the server.

  Embodiments described herein are terrestrial transmitter networks that include a plurality of transmitters that broadcast positioning signals that include at least ranging signals and positioning system information, wherein the ranging signals broadcast ranging signals. A terrestrial transmitter network that includes information used to measure the distance to the transmitter to be transmitted and a remote receiver that obtains at least one of a positioning signal and a satellite signal, the remote receiver comprising: Temporarily using one of the plurality of native receive chains of the remote receiver to obtain at least one of the positioning signal and the satellite signal, the satellite signal is a satellite-based positioning system The first mode of operation of the remote receiver is that the remote receiver has a small number of positioning signals and satellite signals. A remote receiver and a server coupled to the remote receiver, including a terminal-based positioning that calculates the position of the remote receiver from at least one, wherein the second operating mode of the remote receiver is determined by the server positioning Network-based positioning that calculates a position of the remote receiver from information derived from at least one of the signal and the satellite signal, wherein the remote receiver receives at least one of the positioning signal and the satellite signal. And a positioning system including a server for transferring information derived therefrom to the server.

  The remote receiver of an embodiment temporarily uses one native receive chain of the remote receiver's multiple native receive chains to acquire at least one of the positioning signal and the satellite signal.

  The multiple native receive chains of one embodiment include diversity receive chains that improve receive diversity.

  The remote receiver of one embodiment includes a wideband receiver.

  The remote receiver of one embodiment includes a broadband cellular band receiver.

  The remote receiver of one embodiment uses a diversity receive chain to acquire a positioning signal at least one of temporary and permanent.

  The systems described herein for use in position / timing accuracy are for asset management, human tracking, pet tracking, fire protection, mobile advertising, public security applications, both in local and wide areas. Ad hoc position determination (e.g., a set of "mobile" transmitters can be moved to a location (e.g., a fire location), which sends a location signal to a set of nearby receivers. Form a local network to provide), military applications (eg, transmitters can be deployed on land or wirelessly in ad hoc form to obtain accurate indoor locations), accuracy of Adaptable bandwidth for applications that can provide bandwidth that meets your needs, container tracking and moving containers around in indoor environments Pallet tracking, femtocell, femtocell timing reference, timing receiver, indoor and outdoor for vehicles, geotagging, geofencing, E911 applications, medical applications and other applications requiring pallet tracking Providing locations for security applications that authenticate based on both locations, homing applications (eg, providing pet / asset tracking using WAPS, and providing pedestrian navigation to assets / pets using mobile phones) It can be used in one or more of the applications, but is not limited to these applications. A WAPS system, either alone or integrated with other location technologies, can be further integrated into existing local and / or wide area asset management and / or positioning systems.

  Embodiments described herein are a transmitter network that includes a plurality of transmitters that broadcast signals, and a remote receiver that acquires and tracks at least one of positioning signals and satellite signals, The satellite signal is a signal of a satellite-based positioning system, and the first mode of operation of the remote receiver is a terminal-based where the remote receiver calculates the position of the remote receiver from at least one of the positioning signal and the satellite signal. And a server coupled to the remote receiver, wherein the second mode of operation of the remote receiver is such that the server determines the position of the remote receiver from at least one of the positioning signal and the satellite signal. Including a network-based positioning, wherein the remote receiver receives at least one of the positioning signal and the satellite signal. Transferring information to the server, including a positioning system including a server.

  Embodiments described herein are methods for determining a position, wherein a remote receiver receives at least one of a positioning signal and a satellite signal, wherein the positioning signal includes a plurality of transmissions. The satellite signal is received from a satellite-based positioning system and the remote receiver using one of terminal-based positioning and network-based positioning Determining the position of the mobile terminal based positioning comprises calculating the position of the remote receiver at the remote receiver using at least one of the positioning signal and the satellite signal, Positioning includes calculating the position of the remote receiver at the remote server using at least one of the positioning signal and the satellite signal. , The method comprising metropolitan determining step.

  The components described herein can be placed together or in separate locations. A communication path includes any medium that couples components and communicates or transfers files between components. Communication paths include wireless connections, wired connections, and hybrid wireless / wired connections. Communication paths also include connections or connections to networks including local area networks (LANs), metropolitan area networks (MANs), wide area networks (WANs), proprietary networks, inter-office or back-end networks, and the Internet. In addition, communication paths include removable fixed media such as floppy disks, hard disk drives, and CD-ROM disks, as well as flash RAM, Universal Serial Bus (USB) connections, RS-232 connections, telephone lines, buses, and email messages. including.

  Aspects of the systems and methods described herein include field programmable gate arrays (FPGAs), programmable array logic (PAL) devices, electrically programmable logic devices, electrically programmable memory devices, and It can be implemented as a programmed function in any of a variety of circuits, including programmable logic devices (PLDs) such as standard cell-based devices, as well as application specific integrated circuits (ASICs). Some other possibilities for implementing aspects of the system and method include a microcontroller having a memory (such as an electronically erasable programmable read only memory (EEPROM)), an embedded microprocessor, firmware, software, and the like. In addition, aspects of the system and method can be implemented as a microprocessor having software-based circuit emulation, discrete logic (sequential and combination), custom devices, fuzzy (neural) logic, quantum devices, and hybrids of any of the above device types. Can be implemented within. Of course, the underlying device technology can be used in various component types, for example, metal oxide field effect transistor (MOSFET) technology such as complementary metal oxide semiconductor (CMOS), bipolar technology such as emitter coupled logic (ECL). , Polymer technology (eg, silicon conjugated polymer structures and metal conjugated polymer metal structures), mixed analog and digital, etc.

  All systems, methods and / or other components disclosed herein may be described using computer-aided design tools, including behavior, register transfer, logic components, transistors, layout shapes, and / or Note that, or for other characteristics, it can be represented (or represented) as data and / or instructions embodied in various computer-readable media. Computer readable media that can implement such formatted data and / or instructions include various forms of non-volatile storage media (eg, optical, magnetic, or semiconductor storage media) and wireless, optical, or wired. Including, but not limited to, any of the signaling media, or any combination thereof, which may be used to transfer such formatted data and / or instructions. Examples of transfer of such formatted data and / or instructions by carrier wave are the Internet and / or other computers via one or more data transfer protocols (eg, HTTP, HTTPs, FTP, SMTP, WAP, etc.) Including but not limited to forwarding over a network (upload, download, email, etc.). Such database representations and / or instruction-based representations of the components described above when received within a computer system via one or more computer-readable media are one or more other computer programs. May be processed by a processing entity (eg, one or more processors) within the computer system.

  Unless the context clearly requires otherwise, the words “comprise”, “comprising”, etc. are not meant to be exclusive or exhaustive throughout the specification and claims. Should be interpreted in a comprehensive sense, that is, in the sense of “including but not limited to”. Words using the singular or plural number also include the plural or singular number respectively. Further, the words “in this specification”, “below”, “above”, “below”, and like-meaning terms, as referred to in this application, refer to the whole rather than any particular part of this application. As the present application. When the word “or” is used with respect to a list of two or more items, the word can be any of the items in the list, all of the items in the list, and any combination of the items in the list; Includes all interpretations of the word.

  The above description of embodiments of the system and method is not intended to be exhaustive, nor is it intended to limit the system and method to the precise forms disclosed. Certain embodiments of the system and method and examples thereof are described herein for purposes of illustration, and as those skilled in the art will appreciate, various equivalent modifications are possible within the scope of the system and method. . The teachings of the present systems and methods provided herein can be applied not only to the systems and methods described above, but also to other systems and methods. The elements and acts of the various embodiments described above can be combined to provide further embodiments. These and other changes can be made to the system and method in light of the above detailed description.

  In general, in the following claims, the terminology used should not be construed as limiting the system and method to the specific embodiments disclosed in the specification and the claims, Should be construed to include all systems and methods operating under the scope of Accordingly, the systems and methods are not limited by the present disclosure, the scope of which must be determined entirely by the claims. Although certain aspects of the present systems and methods are presented below in the form of certain claims, the inventors contemplate the various aspects of the systems and methods in any number of claims. . Accordingly, the inventors reserve the right to add additional claims after filing this application in order to pursue additional claim forms for other aspects of the system and method.

Claims (162)

A ground transmitter network including a plurality of transmitters that broadcast a positioning signal including at least a ranging signal and positioning system information, the ranging signal measuring a distance to a transmitter that broadcasts the ranging signal. A terrestrial transmitter network containing information used for
A reference sensor array including at least one reference sensor unit positioned at a known location;
A remote receiver including an atmospheric sensor to collect atmospheric data at the remote receiver location;
A positioning application running on a processor and coupled to the remote receiver, the positioning application including the atmospheric data, reference data from a set of reference sensor units of the reference sensor array, and the positioning signal and satellite A positioning system comprising: a positioning application, wherein the position of the remote receiver is calculated using information derived from at least one of the satellite signals that are signals of the base positioning system, the position including an elevation; . A ground transmitter network including a plurality of transmitters that broadcast a positioning signal including at least a ranging signal and positioning system information, the ranging signal measuring a distance to a transmitter that broadcasts the ranging signal. A terrestrial transmitter network containing information used for
A reference sensor array including at least one reference sensor unit positioned at a known location;
A remote receiver including an atmospheric sensor that collects atmospheric data at the location of the remote receiver;
A positioning application running on a processor and coupled to the remote receiver, the positioning application using the atmospheric data and reference data from a set of reference sensor units of the reference sensor array, Generating a reference pressure estimate at the position of the receiver, wherein the positioning application is derived from at least one of the reference pressure estimate and a satellite signal that is a signal of the positioning signal and a satellite-based positioning system; A positioning system including a positioning application using said information to calculate the position of the remote receiver, the position including an elevation.   The positioning system according to claim 2, wherein the positioning application is hosted on the remote receiver, and the remote receiver calculates the position.   The positioning system of claim 3, wherein the remote receiver operates in a powered down state when the positioning signal is at least one of undetected and unusable.   The remote receiver uses a set of positioning signals from the plurality of transmitter sets to determine a position, and the remote receiver has at least one of the set of positioning signals not detected and unusable. 5. The positioning system according to claim 4, wherein when the number is one, the system operates with the power reduced.   The remote receiver is powered off in response to detecting at least one of movement of the remote receiver, a change in the position of the remote receiver, and a change in signal condition of the positioning signal. The positioning system according to claim 5, wherein the positioning system transitions to a full power state.   The positioning system of claim 2, including a server coupled to the remote receiver, wherein the positioning application is hosted on the server, and the server calculates the location.   The positioning system of claim 2, comprising a server coupled to the remote receiver, wherein the positioning application is distributed between the remote receiver and the server.   The positioning system of claim 8, wherein the first mode of operation of the remote receiver includes terminal-based positioning in which the remote receiver calculates the position.   9. The positioning system of claim 8, wherein the second mode of operation of the remote receiver includes network based positioning where the server calculates the location.   The positioning system according to claim 2, wherein the known location is a location of a set of transmitters of the plurality of transmitters.   3. The positioning application of claim 2, wherein the positioning application includes a pressure surface gradient model that uses the reference data from the set of reference sensor units to generate an equivalent reference elevation pressure at the location of the remote receiver. Positioning system.   The positioning system according to claim 12, wherein the positioning application uses the equivalent reference elevation pressure as a reference value for generating the elevation.   The positioning system of claim 12, wherein the positioning application generates an equivalent reference elevation pressure for each reference sensor unit of the set of reference sensor units using the reference data from each reference sensor unit.   15. The positioning system of claim 14, wherein the reference data includes pressure data, temperature data, and location data for each reference sensor unit in the set of reference sensor units, and the location data includes elevation.   The positioning application uses the equivalent reference elevation pressure of each reference sensor unit of the set of reference sensor units and the latitude and longitude of the remote receiver to use the equivalent reference elevation pressure at the location of the remote receiver. 16. The positioning system according to claim 15, wherein   17. The positioning system of claim 16, wherein the positioning application generates the elevation of the remote receiver using the atmospheric data and the equivalent standard elevation pressure at the location of the remote receiver.   The positioning system according to claim 2, wherein the at least one reference sensor unit is arranged at the same position as at least one transmitter of the plurality of transmitters.   The at least one reference sensor unit includes a plurality of reference sensor units, and the first set of the plurality of reference sensor units is disposed at the same position as the first set of the plurality of transmitters. The positioning system of claim 2, wherein the second set of units is located at a location different from the plurality of locations.   The positioning system according to claim 2, wherein the at least one reference sensor unit is at a location different from locations of the plurality of transmitters.   The positioning system according to claim 2, wherein the atmospheric sensor collects pressure data and temperature data at the position of the remote receiver.   The positioning system of claim 21, wherein the atmospheric sensor determines the pressure data with a resolution in a range of less than about 36 Pascals.   The positioning system according to claim 21, wherein the remote receiver detects a rate of change of the pressure data.   24. The positioning system of claim 23, wherein the positioning application uses the rate of change to determine the vertical speed of the remote receiver.   The temperature data includes outside temperature at the location of the remote receiver, and the atmospheric sensor determines the temperature data with a resolution of at least one equal to and less than about 3 degrees Celsius. The positioning system according to 21.   The positioning system of claim 2, wherein each reference sensor unit includes at least one atmospheric reference sensor that collects reference pressure data and reference temperature data at known locations of the atmospheric reference unit.   27. The positioning system of claim 26, wherein the at least one atmospheric reference sensor determines the reference pressure data with a resolution within a range of about 2 to 36 Pascals.   27. The reference temperature data includes an ambient temperature at the known location, and the atmospheric reference sensor determines the temperature data with a resolution of at least one equal to and less than about 3 degrees Celsius. The positioning system described in.   27. The positioning system of claim 26, wherein the atmospheric reference sensor is calibrated for a limited temperature range, and the limited temperature range is determined based on a temperature to which the atmospheric reference sensor is exposed.   27. The positioning system of claim 26, wherein each atmospheric reference sensor continuously collects the reference pressure data and the reference temperature data at the known location.   27. The positioning system of claim 26, wherein the atmospheric reference sensor is positioned to collect the reference pressure and the reference temperature in relatively static air.   27. The positioning system of claim 26, wherein the atmospheric reference sensor filters the reference pressure data and the reference temperature data.   The positioning system of claim 32, wherein the atmospheric reference sensor filters the reference pressure data and the reference temperature data using an adaptive time scale.   27. The positioning system of claim 26, wherein each reference sensor unit includes a wind detector that determines wind data, and the wind data includes a local wind direction and intensity.   35. The positioning system of claim 34, wherein the positioning application uses the wind data to perform at least one of correction and filtering of variations in the atmospheric sensor.   27. The positioning system of claim 26, wherein the at least one reference sensor unit includes a plurality of atmospheric reference sensors.   The positioning system of claim 2 including a communication link coupled between the reference sensor array and the remote receiver.   38. The positioning system of claim 37, wherein the reference sensor array broadcasts atmospheric reference data.   40. The positioning system of claim 38, wherein the reference sensor array broadcasts raw data of the atmospheric reference data.   The positioning system according to claim 38, wherein the reference sensor array broadcasts difference data of the reference data.   41. The positioning system of claim 40, wherein the difference data is derived relative to at least one constant value.   The positioning system according to claim 40, wherein the differential data includes differential pressure data derived as an offset value of a standard atmosphere.   40. The positioning system of claim 38, wherein the remote receiver receives the reference data via the broadcast.   40. The positioning system of claim 38, wherein the reference sensor array broadcasts the reference data multiple times per second.   40. The positioning system of claim 38, wherein the reference sensor array broadcasts the reference data multiple times per measurement.   38. The positioning system of claim 37, wherein the remote receiver determines a set of atmospheric reference sensors to be queried and pulls the reference data from the set of atmospheric reference sensors via the communication link.   The positioning system according to claim 2, wherein the positioning application processes the reference data to determine an equivalent reference elevation pressure for each reference sensor unit of the set of reference sensor units.   48. The positioning system of claim 47, wherein the reference data includes a location for each atmospheric reference unit.   49. The positioning system of claim 48, wherein the location includes latitude and longitude.   49. The positioning system of claim 48, wherein the location includes a height.   48. The positioning system of claim 47, wherein the reference data includes a measured outside temperature from each atmospheric reference unit.   48. The positioning system of claim 47, wherein the reference data includes a confidence measure.   The positioning system according to claim 2, wherein each reference sensor unit processes the reference data of the reference sensor unit and determines an equivalent reference altitude pressure of the reference sensor unit.   54. The positioning system of claim 53, wherein the reference data includes a location for each atmospheric reference sensor.   55. The positioning system of claim 54, wherein the location includes latitude and longitude.   55. The positioning system of claim 54, wherein the location includes a height.   54. The positioning system according to claim 53, wherein the reference data includes the equivalent reference elevation pressure.   54. The positioning system of claim 53, wherein the reference data includes a confidence measure.   The positioning system according to claim 2, wherein the elevation includes an estimated elevation of each floor in at least one structure.   60. The positioning system of claim 59, including a database coupled to a plurality of remote receivers including the remote receiver, the database including the estimated elevation received from the plurality of remote receivers.   61. A learning application coupled to the server, wherein the learning application processes the estimated elevations of the plurality of remote receivers and revises the database using the estimated elevations. The positioning system described in.   The positioning system of claim 2, wherein the at least one reference sensor unit includes at least one local reference sensor unit local to at least one of location and structure.   64. The positioning system of claim 62, wherein the reference data includes data of the at least one local reference sensor unit.   3. The positioning system of claim 2, comprising automatically calibrating the atmospheric sensor of the remote receiver using reference data aggregated over a specified time period.   Generating the aggregated reference data by identifying when the remote receiver is at a known location; accumulating deviations in the atmospheric data corresponding to the known location; 66. The positioning system of claim 64, comprising generating a corrected calibration from the calculated deviation.   3. The positioning system of claim 2, comprising automatically calibrating the atmospheric sensor of the remote receiver when the altitude and atmospheric pressure of the position of the remote receiver are known.   68. The positioning system of claim 66, wherein the position of the remote receiver is determined using the satellite signal.   The positioning system according to claim 2, comprising determining the elevation using a reference elevation.   69. The positioning system of claim 68, wherein the reference elevation minimizes an elevation difference between elevations calculated using at least one of the atmospheric data and the reference data.   The positioning system according to claim 69, wherein the reference elevation includes an average elevation of the atmospheric reference unit.   70. The positioning system of claim 69, wherein the reference elevation includes an average elevation of an area where the remote receiver is located.   The positioning system of claim 2, wherein the elevation includes an estimated elevation derived using local constraint data.   The positioning system of claim 72, wherein the local constraint data includes terrain data of terrain near the location of the remote receiver.   The positioning system of claim 72, wherein the local constraint data includes a height of at least one structure near the location of the remote receiver.   The positioning system of claim 72, wherein the local constraint data includes the elevation of at least one other remote receiver in the vicinity of the location of the remote receiver.   The positioning system according to claim 72, wherein the positioning application determines the elevation using the atmospheric data, the reference data, and the local constraint data.   Including a database coupled to the positioning application, the database including historical data measured during a time period, the historical data including the reference data of the reference sensor array and the atmospheric data of a plurality of remote receivers. The positioning system according to claim 2, comprising:   The positioning system according to claim 77, wherein the positioning application determines the altitude using the historical data.   78. The positioning system of claim 77, comprising optimizing the at least one reference sensor unit of the reference sensor array using the historical data.   The positioning system of claim 2, comprising determining the elevation by relaxing a constant equivalent reference elevation pressure assumption between a reference location of a reference sensor unit and a current position of the remote receiver. Converting a first equivalent reference elevation pressure at the reference location to a second equivalent reference elevation pressure at a standard temperature;
Determining a local temperature at the current position and using the local temperature to convert the second equivalent reference elevation pressure to a third equivalent reference elevation pressure;
81. The positioning system of claim 80, comprising determining the elevation of the current location using the third equivalent reference elevation pressure. Using the reference data at each reference sensor unit of the set of reference sensor units to determine a variation in equivalent reference elevation pressure with a horizontal location;
81. The positioning system of claim 80, comprising determining a best estimate of a reference elevation pressure at the current location by combining the equivalent reference elevation pressures of the set of reference sensor units.   Determining the best estimate of equivalent reference elevation pressure includes using a weighted average technique, wherein the weight is a function of a horizontal distance between a reference sensor unit location and the current position. Item 83. The positioning system according to Item 82.   Determining the best estimate of equivalent reference elevation pressure is a least squares fit to create a secondary surface that best fits the calculated sea level pressure at each reference sensor unit in the set of reference sensor units. 83. The positioning system of claim 82, comprising using and interpolating the best estimate of equivalent reference elevation pressure at the current location using an nth order surface. Converting a first equivalent reference elevation pressure at each reference sensor unit of the set of reference sensor units into a second equivalent reference elevation pressure at a standard temperature;
81. The positioning system of claim 80, comprising determining a best estimate of equivalent reference elevation pressure at the current location by combining the second equivalent reference elevation pressures from each reference unit.   Determining the best estimate of equivalent reference elevation pressure includes using a weighted average technique, wherein the weight is a function of a horizontal distance between a reference sensor unit location and the current position. Item 86. The positioning system according to Item 85.   Determining the best estimate of equivalent reference altitude pressure is the least square to produce a secondary surface that best fits the calculated equivalent reference altitude pressure at each reference sensor unit of the set of reference sensor units. 86. The positioning system of claim 85, comprising using a fit and interpolating the best estimate of sea level pressure at the current location using an nth order surface.   The positioning system according to claim 2, wherein the remote receiver includes a high-speed clock.   The remote receiver receives pulse edges from a common time reference, and the remote receiver uses the high speed clock to determine the time difference between the occurrence of the pulse edge and the rising edge of the sample clock. 90. A positioning system according to claim 88.   90. The positioning system of claim 89, wherein the remote receiver applies a correction to an estimated distance based on the time difference, and the correction improves the accuracy of the estimated distance.   The remote receiver includes a correlator that correlates a received signal with a pseudo-random code, and the correlator includes a first shift register including a plurality of serial sets of second shift registers having parallel random access read capability. The positioning system according to claim 2.   92. The positioning system of claim 91, wherein each set of the plurality of sets of second shift registers includes a plurality of serial shift register group primitives.   94. The positioning system of claim 92, wherein each shift register group primitive includes an n-bit shift register group primitive.   94. The positioning system of claim 93, wherein each shift register group primitive comprises a 16 bit shift register group primitive.   94. The positioning system of claim 92, wherein each set of second shift registers forms a 32-bit shift register.   94. The positioning system of claim 92, wherein the plurality of serial shift sets of second shift registers includes a plurality of sets of n-bit shift registers.   99. The positioning system of claim 96, wherein the plurality of serial sets of second shift registers includes 32 sets of second shift registers, and the first shift register is a 1024 bit shift register.   98. The positioning system of claim 97, wherein the shift operation of the first shift register occurs at a clock rate of a clock coupled to the correlator.   99. The positioning system of claim 98, wherein the read operation of the first shift register occurs at a rate that is at least twice the clock rate.   The positioning system according to claim 99, wherein the read operation of the first shift register occurs at 32 times the clock rate.   97. The positioning system of claim 96, comprising a plurality of serial adders coupled to the output of the series sets of second shift registers.   102. The positioning system of claim 101, wherein the plurality of serial adders includes an adder tree, and the adder tree includes a wider bit width adder primitive.   102. The positioning system of claim 101, wherein the plurality of serial adders includes an adder coupled to each set of the plurality of sets of n-bit shift registers.   The plurality of serial adders includes a first adder coupled to the output of the first plurality of sets of second shift registers and a second adder coupled to the output of the second plurality of sets of second shift registers. And a third adder coupled to the output of the third plurality of sets of second shift registers and a fourth adder coupled to the output of the fourth plurality of sets of second shift registers. 103. The positioning system according to 103.   102. The positioning system of claim 101, comprising a termination adder coupled to the output of the plurality of adders in series.   106. The positioning system of claim 105, comprising aligning the outputs of the series adders in a series group in the termination adder.   In the termination adder, the output of the first adder is aligned within the first group, the output of the second adder is aligned within the second group, and the output of the third adder is the third 107. The positioning system of claim 106, aligned within the group and the output of the fourth adder is aligned within the fourth group.   107. The positioning system of claim 106, wherein the end adder forms a sum by adding the contents of the series groups.   The remote receiver temporarily uses a native receive chain of a plurality of native receive chains of the remote receiver to obtain the at least one of the positioning signal and satellite signal; The positioning system according to claim 2.   110. The positioning system of claim 109, wherein the plurality of native receive chains includes a diversity receive chain that improves receive diversity.   111. The positioning system of claim 110, wherein the remote receiver comprises a broadband receiver.   112. The positioning system of claim 111, wherein the remote receiver comprises a wideband cellular band receiver.   111. The positioning system of claim 110, wherein the remote receiver uses the diversity receive chain to acquire the positioning signal at least one of temporary and permanent.   The positioning system of claim 2, including a communication system coupled to at least one of the remote receiver and the plurality of transmitters, wherein the communication system is a cellular communication system.   The positioning system according to claim 2, wherein the plurality of transmitters are synchronized, and each transmitter of the plurality of transmitters transmits a signal including a pseudo-random sequence and assistance data.   The assistance data includes a system time at a rising edge of a waveform pulse, a system time at a falling edge of a waveform pulse, geocode data of the plurality of transmitters, and a geocode of an adjacent transmitter adjacent to the plurality of transmitters. Data, index of sequence used by at least one transmitter in the vicinity of the plurality of transmitters, clock timing correction of at least one transmitter, local atmospheric correction, relationship of WAPS timing to GNSS time, pseudorange resolution An indication of the local environment to assist the remote receiver, as well as an offset from the base index of the set of pseudo-random sequences, a list of pseudo-random sequences from the set of transmitters, and a list of transmitters that utilize a particular pseudo-random sequence Out of Comprising at least one of the at least one positioning system according to claim 115.   The positioning application formulates a set of equations as a non-linear objective function and generates a best estimate of the position as a set of position parameters that minimizes the objective function, thereby allowing the remote receiver to The positioning system according to claim 2, wherein the position is calculated.   The positioning application calculates the position of the remote receiver by formulating a set of linearized equations and solving the set of linearized equations using a least squares method. The positioning system according to claim 2.   The positioning application calculates the position of the remote receiver using an approximate location of a transmitter set of the plurality of transmitters and received signal strength (RSS) data of the set of transmitters. 2. The positioning system according to 2.   The positioning application stores sample segments of the positioning signal in the remote receiver and then processes the sample segments to retrieve, obtain and calculate distances to the plurality of transmitters The positioning system according to claim 2, wherein the position of the remote receiver is calculated.   The positioning system of claim 2, wherein the positioning application calculates the position of the remote receiver using received signal strength data of the remote receiver.   The positioning system according to claim 2, wherein the positioning application calculates the position of the remote receiver using at least one of carrier phase data and code phase data of the positioning signal.   The positioning system of claim 2, wherein the positioning application calculates the position of the remote receiver using differential positioning relative to at least one reference receiver.   The positioning application calculates the position of the remote receiver using at least one of a distance measurement and a distance measurement surrogate from an opportunity signal, the opportunity signal comprising a positioning system, 3. Received from a global navigation satellite system (GNSS), a global positioning system (GPS), a differential positioning system, a radio signal, a television signal, a wireless network system, a WiFi system, a cellular system, and a Bluetooth system. The positioning system described in.   The positioning application uses a distance measurement from at least one additional signal source combined with a distance measurement determined using the positioning signal to calculate a final position of the remote receiver. The positioning system according to claim 2, wherein the final position includes at least one of latitude, longitude, and height.   The positioning application includes a position measurement from at least one additional signal source combined with a position measurement determined using the positioning signal, and a position quality metric from the at least one additional signal source. The positioning system of claim 2, wherein the positioning system is used to calculate an optimized location solution for the remote receiver.   The positioning application uses hybrid positioning to calculate the position of the remote receiver, the hybrid positioning including measurements from the positioning signal and measurements from at least one additional source; The positioning system according to claim 2.   The positioning system according to claim 2, wherein the positioning system information includes timing synchronization information and corresponding correction information. A reference sensor array comprising at least one set of reference sensor units, each set comprising at least one reference sensor unit positioned at a known location;
A remote receiver including an atmospheric sensor that collects atmospheric data at the location of the remote receiver;
A positioning application running on a processor and coupled to the remote receiver, the positioning application using the atmospheric data and reference data from the at least one set of reference sensor units of the reference sensor array. A positioning system that generates a reference pressure estimate at the location of the remote receiver, and wherein the positioning application uses the reference pressure estimate to calculate an elevation of the remote receiver. . A ground transmitter network including a plurality of transmitters that broadcast a positioning signal including at least a ranging signal and positioning system information, the ranging signal measuring a distance to a transmitter that broadcasts the ranging signal. A terrestrial transmitter network containing information used for
A remote receiver that acquires at least one of the positioning signal and satellite signal, wherein the satellite signal is a signal of a satellite-based positioning system, and the first operating mode of the remote receiver is the remote receiver A correlator for correlating the received signal with a pseudo-random code, wherein the receiver includes a terminal-based positioning that calculates a position of the remote receiver from at least one of the positioning signal and the satellite signal Including a remote receiver,
A server coupled to the remote receiver, wherein the second mode of operation of the remote receiver is such that the server is derived from information derived from at least one of the positioning signal and the satellite signal. Including a network-based positioning that calculates a position of the remote receiver, wherein the remote receiver receives at least one of the positioning signal and the satellite signal and forwards information derived therefrom to the server; Including positioning system.   131. The positioning system of claim 130, wherein the correlator includes a first shift register that includes a plurality of serial sets of second shift registers having parallel random access read capability.   132. The positioning system of claim 131, wherein each set of the plurality of sets of second shift registers includes a plurality of serial shift register group primitives.   135. The positioning system of claim 132, wherein each shift register group primitive includes an n-bit shift register group primitive.   143. The positioning system of claim 133, wherein each shift register group primitive comprises a 16 bit shift register group primitive.   135. The positioning system of claim 132, wherein each set of second shift registers forms a 32-bit shift register.   143. The positioning system of claim 132, wherein the series sets of second shift registers include a plurality of sets of n-bit shift registers.   137. The positioning system of claim 136, wherein the plurality of serial sets of second shift registers includes 32 sets of second shift registers, and the first shift register is a 1024 bit shift register.   138. The positioning system of claim 137, wherein the shift operation of the first shift register occurs at a clock rate of a clock coupled to the correlator.   139. The positioning system of claim 138, wherein the read operation of the first shift register occurs at a rate that is at least twice the clock rate.   140. The positioning system of claim 139, wherein the read operation of the first shift register occurs at 32 times the clock rate.   138. The positioning system of claim 136, comprising a plurality of series adders coupled to the output of the series sets of second shift registers.   142. The positioning system of claim 141, wherein the plurality of serial adders includes an adder tree, and the adder tree includes a wider bit width adder primitive.   142. The positioning system of claim 141, wherein the plurality of serial adders includes an adder coupled to each set of the plurality of sets of n-bit shift registers.   The plurality of serial adders includes a first adder coupled to the output of the first plurality of sets of second shift registers and a second adder coupled to the output of the second plurality of sets of second shift registers. And a third adder coupled to the output of the third plurality of sets of second shift registers and a fourth adder coupled to the output of the fourth plurality of sets of second shift registers. 143. The positioning system according to 143.   142. The positioning system of claim 141, comprising a termination adder coupled to the output of the plurality of adders in series.   146. The positioning system of claim 145, comprising aligning the outputs of the series adders in the series groups in the termination adder.   In the termination adder, the output of the first adder is aligned within the first group, the output of the second adder is aligned within the second group, and the output of the third adder is the third 147. The positioning system of claim 146, aligned within the group and the output of the fourth adder is aligned within the fourth group.   147. The positioning system of claim 146, wherein the termination adder forms a sum by adding the contents of the series groups. A ground transmitter network including a plurality of transmitters that broadcast a positioning signal including at least a ranging signal and positioning system information, the ranging signal measuring a distance to a transmitter that broadcasts the ranging signal. A terrestrial transmitter network containing information used for
A remote receiver that acquires at least one of the positioning signal and satellite signal, wherein the satellite signal is a signal of a satellite-based positioning system, and the first operating mode of the remote receiver is the remote receiver The receiver includes a terminal based positioning that calculates a position of the remote receiver from at least one of the positioning signal and the satellite signal, the remote receiver being powered down when the positioning signal is not detected A remote receiver that operates in
A server coupled to the remote receiver, wherein the second mode of operation of the remote receiver is such that the server is derived from information derived from at least one of the positioning signal and the satellite signal. Including a network-based positioning that calculates a position of the remote receiver, wherein the remote receiver receives at least one of the positioning signal and the satellite signal and forwards information derived therefrom to the server; Including positioning system.   149. The positioning system of claim 149, wherein the positioning application is hosted on the remote receiver, and the remote receiver calculates the location.   161. The positioning system of claim 150, wherein the remote receiver operates in a powered down state when the positioning signal is at least one of undetected and unusable.   The remote receiver uses a set of positioning signals from the plurality of transmitter sets to determine a position, and the remote receiver has at least one of the set of positioning signals not detected and unusable. 154. The positioning system of claim 151, wherein when operated, the system operates with reduced power.   The remote receiver is powered off in response to detecting at least one of movement of the remote receiver, a change in the position of the remote receiver, and a change in signal condition of the positioning signal. 157. The positioning system of claim 152, transitioning to a full power state. A ground transmitter network including a plurality of transmitters that broadcast a positioning signal including at least a ranging signal and positioning system information, the ranging signal measuring a distance to a transmitter that broadcasts the ranging signal. A terrestrial transmitter network containing information used for
A remote receiver that acquires at least one of the positioning signal and satellite signal, wherein the satellite signal is a signal of a satellite-based positioning system, and the first operating mode of the remote receiver is the remote receiver A remote receiver including a terminal based positioning for calculating a position of the remote receiver from at least one of the positioning signal and the satellite signal, the remote receiver including a high speed clock;
A server coupled to the remote receiver, wherein the second mode of operation of the remote receiver is such that the server is derived from information derived from at least one of the positioning signal and the satellite signal. Including a network-based positioning that calculates a position of the remote receiver, wherein the remote receiver receives at least one of the positioning signal and the satellite signal and forwards information derived therefrom to the server; Including positioning system.   The remote receiver receives pulse edges from a common time reference, and the remote receiver uses the high speed clock to determine the time difference between the occurrence of the pulse edge and the rising edge of the sample clock. 154. The positioning system according to claim 154.   165. The positioning system of claim 155, wherein the remote receiver applies a correction to an estimated distance based on the time difference, and the correction improves the accuracy of the estimated distance. A ground transmitter network including a plurality of transmitters that broadcast a positioning signal including at least a ranging signal and positioning system information, the ranging signal measuring a distance to a transmitter that broadcasts the ranging signal. A terrestrial transmitter network containing information used for
A remote receiver for acquiring at least one of the positioning signal and satellite signal, wherein the remote receiver receives the remote reception to acquire the at least one of the positioning signal and satellite signal. One of the plurality of native receive chains of the receiver is temporarily used, the satellite signal is a signal of a satellite-based positioning system, and the first operation mode of the remote receiver is the remote receiver A remote receiver, wherein the receiver includes a terminal-based positioning that calculates a position of the remote receiver from at least one of the positioning signal and the satellite signal;
A server coupled to the remote receiver, wherein the second mode of operation of the remote receiver is such that the server is derived from information derived from at least one of the positioning signal and the satellite signal. Including a network-based positioning that calculates a position of the remote receiver, wherein the remote receiver receives at least one of the positioning signal and the satellite signal and forwards information derived therefrom to the server; Including positioning system.   The remote receiver temporarily uses a native receive chain of a plurality of native receive chains of the remote receiver to obtain the at least one of the positioning signal and satellite signal; 158. The positioning system according to claim 157.   159. The positioning system of claim 158, wherein the plurality of native receive chains includes a diversity receive chain that improves receive diversity.   160. The positioning system of claim 159, wherein the remote receiver comprises a broadband receiver.   164. The positioning system of claim 160, wherein the remote receiver comprises a wideband cellular band receiver.   160. The positioning system of claim 159, wherein the remote receiver uses the diversity receive chain to acquire the positioning signal at least one of temporary and permanent.

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