US20140266905A1 - Methods and apparatus for improving time of arrival determination - Google Patents

Methods and apparatus for improving time of arrival determination Download PDF

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US20140266905A1
US20140266905A1 US14/207,432 US201414207432A US2014266905A1 US 20140266905 A1 US20140266905 A1 US 20140266905A1 US 201414207432 A US201414207432 A US 201414207432A US 2014266905 A1 US2014266905 A1 US 2014266905A1
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Prior art keywords
arrival
signal
receiver
determining
eigenvalues
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English (en)
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Andrew Sendonaris
Norman F. Krasner
Jagadish Venkataraman
Chen Meng
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Nextnav LLC
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Nextnav LLC
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Publication of US20140266905A1 publication Critical patent/US20140266905A1/en
Assigned to NEXTNAV, LLC reassignment NEXTNAV, LLC CORRECTIVE ASSIGNMENT TO CORRECT THE TITLE INSIDE THE ASSIGNMENT DOCUMENT PREVIOUSLY RECORDED AT REEL: 032434 FRAME: 0634. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Assignors: KRASNER, NORMAN, MENG, Chen, SENDONARIS, ANDREW, VENKATARAMAN, JAGADISH
Assigned to NEXTNAV, LLC reassignment NEXTNAV, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: KRASNER, NORMAN F, SENDONARIS, ANDREW, MENG, Chen, VENKATARAMAN, JAGADISH
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S1/00—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith
    • G01S1/02—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith using radio waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S1/00—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith
    • G01S1/02—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith using radio waves
    • G01S1/04—Details
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/22—Multipath-related issues
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0205—Details
    • G01S5/0218—Multipath in signal reception
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0205—Details
    • G01S5/0236—Assistance data, e.g. base station almanac

Definitions

  • This disclosure relates generally to positioning systems. More specifically, but not exclusively, the disclosure relates to devices, systems, and methods for signal processing for high accuracy position/location determination in a wide area positioning system (WAPS) using calculated eigenvalues corresponding to received signals and eigenvalues corresponding to noise.
  • WAPS wide area positioning system
  • Radio-bases systems such as LORAN, GPS, GLONASS, and the like have been used to provide position information for persons, vehicles, equipment, and the like.
  • these systems do, however, have limitations associated with factors such as signal blockage and multipath.
  • This disclosure relates generally to positioning systems. More specifically, but not exclusively, the disclosure relates to devices, systems, and methods for signal processing for high accuracy position/location determination in a wide area transmitter array location system.
  • the disclosure relates to a method of determining location information in a receiver such as a cellular phone, tablet, or other mobile or computing device and/or storing the information and/or providing the information to a user or other electronic computing system or device.
  • the method may include, for example, receiving a positioning signal from a transmitter.
  • the received positioning signal may include a direct path signal component.
  • the received positioning signal may further include one or more multipath signal components.
  • the direct path signal component may be stronger than the multipath signal components in some environments. Alternately, one or more of the multipath signal components may be stronger than the direct path signal component.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • the method may further include computing an estimated covariance of the received positioning signal, determining a set of eigenvalues of the estimated covariance, and estimating a statistical distribution of the eigenvalues.
  • the method may further include an improved method for separating the set of eigenvalues, based on a threshold, into a first subset of eigenvalues corresponding to a transmitted signal including the direct path signal component and the multipath signal components and a second set of eigenvalues corresponding to noise components.
  • the threshold may be based at least in part on the estimated statistical distribution.
  • the two sets of eigenvalues and associated eigenvectors may be used to estimate a time of arrival of the direct path signal component.
  • the method may further include determining, based at least in part on the two sets of eigenvalues and associated eigenvectors, a distance estimate between the transmitter and the receiver.
  • the determining a distance estimate may be based at least in part on the separation of the eigenvalues into the two sets.
  • the disclosure relates to a method of determining location information in a receiver and/or storing the information and/or providing the information to a user or other electronic computing system or device.
  • the method may include, for example, receiving a positioning signal from a transmitter.
  • the positioning signal may include a direct path signal component and one or more multipath signal components.
  • the direct path signal component may be stronger than the multipath signal components in some environments. Alternately, one or more of the multipath signal components may be stronger than the direct path signal component.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • the method may further include computing a statistic of the received positioning signal, computing an estimated covariance of the received positioning signal, determining, if the statistic is within a first range, an estimated time of arrival of the direct path signal using a first method, determining, if the statistic is within a second range, an estimated time of arrival of the direct path signal using a second method, and determining, based at least in part on the estimated time of arrival, a distance estimate between the transmitter and the receiver.
  • the disclosure relates to a method of determining location information in a receiver and/or storing the information and/or providing the information to a user or other electronic computing system or device.
  • the method may include, for example, receiving a positioning signal from a transmitter.
  • the positioning signal may include a direct path signal and one or more multipath signals.
  • the direct path signal may be stronger than the multipath signal in some environments. Alternately, one or more of the multipath signals may be stronger than the direct path signal.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • the method may further include determining an estimated covariance of the received positioning signal, and determining a set of eigenvalues and eigenvectors (so-called eigenvalue decomposition) of the estimated covariance.
  • the method may further include determining a set of potential times of arrival of the positioning signal components, and selecting a first time of arrival value from the set of potential times of arrival.
  • the method may further include determining the value of a quality metric based on information associated with the selected first time of arrival.
  • the method may further include removing the selected first time of arrival from the set of potential times of arrival if the quality metric value is below a predefined threshold to generate a adjusted set of potential times of arrival and repeating the selecting, determining the value of a quality metric, and removing additional selected first times of arrival until the quality metric value is above the predefined threshold.
  • the method may further include determining a distance between the transmitter and receiver from the adjusted set of potential times of arrival.
  • the disclosure relates to devices, modules, and systems for implementing the above-described methods, in whole or in part.
  • the disclosure relates to means to implement the above-described methods, in whole or in part.
  • the disclosure relates to computer readable media including instructions to cause a programmable device such as a general or special purpose processor or other computing device or system to implement or control the above-described methods, in whole or in part.
  • a programmable device such as a general or special purpose processor or other computing device or system to implement or control the above-described methods, in whole or in part.
  • FIG. 1 illustrates details of a terrestrial location/positioning system on which embodiments may be implemented
  • FIG. 2 illustrates details of an embodiment of a receiver/user device in accordance with certain aspects
  • FIG. 3A , FIG. 3B , and FIG. 3C illustrate example output signals from an embodiment of a despreading module showing example multipath signal peaks
  • FIG. 4 illustrates details of an Eigenvalue probability density statistics in one embodiment of a receiver/user device in accordance with certain aspects
  • FIG. 5 illustrates details of Eigenvalue probability density statistics in an embodiment of a receiver/user device in accordance with certain aspects
  • FIG. 6 illustrates details of an example embodiment of a time of arrival peak mask for use in a receiver/user device in accordance with certain aspects
  • FIG. 7 illustrates details of an embodiment of a method for determining a distance estimate in accordance with certain aspects
  • FIG. 8 illustrates details of an embodiment of a method for determining a distance estimate in accordance with certain aspects
  • FIG. 9 illustrates details of an embodiment of a method for determining a distance estimate in accordance with certain aspects
  • FIG. 10 illustrates details of an embodiment of a method for determining a distance estimate in accordance with certain aspects
  • FIG. 11 illustrates details of an embodiment of a method for determining a location of a positioning system receiver in accordance with certain aspects
  • FIG. 12 illustrates details of an embodiment of a method for determining a location of a positioning system receiver in accordance with certain aspects
  • FIG. 13 illustrates details of an embodiment of a method for determining a location of a positioning system receiver in accordance with certain aspects
  • FIG. 14A and FIG. 14B illustrate example superresolution output signals from an embodiment of a despreading module.
  • This disclosure relates generally to positioning systems. More specifically, but not exclusively, the disclosure relates to devices, systems, and methods for providing signaling for position determination and determining high accuracy position/location information using a wide area transmitter array in communication with receivers and processing elements in user devices or terminals (UEs) such as in cellular phones or other portable devices.
  • UEs user devices or terminals
  • the disclosure relates to a method of determining location information in a receiver such as a cellular phone, tablet, or other mobile or computing device and/or storing the information and/or providing the information to a user or other electronic computing system or device.
  • the method may include, for example, receiving a positioning signal from a transmitter.
  • the received positioning signal may include a direct path signal component.
  • the received positioning signal may further include one or more multipath signal components.
  • the direct path signal component may be stronger than the multipath signal components in some environments. Alternately, one or more of the multipath signal components may be stronger than the direct path signal component.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • the method may further include computing an estimated covariance of the received positioning signal, determining an eigenvalue decomposition of the estimated covariance, and estimating a statistical distribution of the eigenvalues.
  • the method may further include an improved method for separating the set of eigenvalues, based on a threshold, into a first subset of eigenvalues corresponding to a transmitted signal including the direct path signal component and the multipath signal components and a second set of eigenvalues corresponding to noise components.
  • the threshold may be based at least in part on the estimated statistical distribution.
  • One or both of the two sets of eigenvalues and associated eigenvectors may be used to estimate a time of arrival of the direct path signal component.
  • the method may further include determining, based at least in part on one or both of the two sets of eigenvalues and associated eigenvectors, a distance estimate between the transmitter and the receiver.
  • the determining a distance estimate may be based at least in part on the separation of the eigenvalues into the two sets.
  • the first set of eigenvalues and associated eigenvectors (corresponding with the estimated transmitted signal) may be used to estimate the time of arrival and/or distance.
  • the second set of eigenvalues and associated eigenvectors (corresponding with the estimated noise) may be used to estimate the time of arrival and/or distance.
  • the method may further include providing the determined location as an output.
  • the output may be sent/transmitted from the receiver to a wired or wireless communications network, such as a cellular or data network.
  • the communications network may be an emergency response network.
  • the output may be sent to another device or system on the communications network.
  • the output may be provided on an audio output or visual display of the receiver.
  • the location of the receiver may, for example, be determined based on a triangulation procedure utilizing the distance estimate between the receiver and the transmitter.
  • the triangulation may be further based on additional distance estimates determined between two or more additional transmitters and the receiver.
  • the disclosure relates to a processor-readable medium including instructions for causing a computer or other processing element to: compute an estimated covariance of a received positioning signal, wherein the received positioning signal includes a direct path signal component and one or more multipath signal components, determine a set of eigenvalues of the estimated covariance, estimate a statistical distribution of the eigenvalues, separate, based on a threshold based at least in part on the estimated statistical distribution, the set of eigenvalues into a first subset of eigenvalues corresponding to a transmitted signal including the direct path signal component and one or more multipath signal components, and a second set of eigenvalues corresponding to noise components, and determine, based at least in part on one or both of the two sets of eigenvalues and associated eigenvectors, a distance estimate between the transmitter and the receiver.
  • the distance estimate may be based at least in part on the separation of the eigenvalues into the two sets.
  • the first set of eigenvalues and associated eigenvectors (corresponding with the estimated transmitted signal) may be used to estimate distance.
  • the second set of eigenvalues and associated eigenvectors (corresponding with the estimated noise) may be used to estimate the distance.
  • the disclosure relates to a positioning system receiver.
  • the receiver may include, for example, an RF module for receiving a positioning signal including a direct path signal component and one or more multipath signal components.
  • the receiver may include a processing module for determining a set of eigenvalues of the estimated covariance, estimating a statistical distribution of the eigenvalues, separating, based on a threshold based at least in part on the estimated statistical distribution, the set of eigenvalues into a first subset of eigenvalues corresponding to a transmitted signal including the direct path signal components and one or more multipath signal components, and a second set of eigenvalues corresponding to noise components, and determining, based at least in part on one or both sets of the two sets of eigenvalues and associated eigenvectors, a distance estimate between the transmitter and the receiver.
  • the receiver may further include an output module for providing the distance estimate as an output.
  • the distance estimate may be based at least in part on the separation of the eigenvalues into two sets.
  • the first set of eigenvalues and associated eigenvectors (corresponding with the estimated transmitted signal) may be used to estimate distance.
  • the second set of eigenvalues and associated eigenvectors (corresponding with the estimated noise) may be used to estimate the distance.
  • the disclosure relates to a method of determining location information in a receiver and/or storing the information and/or providing the information to a user or other electronic computing system or device.
  • the method may include, for example, receiving a positioning signal from a transmitter.
  • the positioning signal may include a direct path signal component and one or more multipath signal components.
  • the direct path signal component may be stronger than the multipath signal components in some environments. Alternately, one or more of the multipath signal components may be stronger than the direct path signal component.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • the method may further include computing a statistic of the received positioning signal, computing an estimated covariance of the received positioning signal, determining, if the statistic is within a first range, an estimated time of arrival of the direct path signal using a first method, determining, if the statistic is within a second range, an estimated time of arrival of the direct path signal using a second method, and determining, based at least in part on the estimated time of arrival, a distance estimate between the transmitter and the receiver.
  • the first method may, for example, include use of an information theoretic criteria for estimating a number of eigenvalues associated with a signal subspace of the estimated covariance and the number of eigenvalues associated with the noise subspace.
  • the estimated time of arrival may be based on the eigenvectors associated with these subspaces.
  • the first or second method may include use of a statistic of the estimated covariance to estimate a number of eigenvalues in a positioning signal subspace of the estimated covariance and the number of signals associated with the noise subspace, wherein the estimated time of arrival is based on the eigenvectors associated with these subspaces.
  • the statistic may be a measure of a signal-to-noise ratio of the received positioning signal.
  • the method may further include determining, based in part on the distance estimate, a location of the receiver, and providing the determined location as an output.
  • the output may be sent/transmitted from the receiver to a wired or wireless communications network, such as a cellular or data network.
  • the communications network may be an emergency response network.
  • the output may be sent to another device or system on the communications network.
  • the output may be provided on an audio output or visual display of the receiver.
  • the location of the receiver may, for example, be determined based on a triangulation procedure utilizing the distance estimate between the receiver and the transmitter.
  • the triangulation may be further based on additional distance estimates determined between two or more additional transmitters and the receiver.
  • the disclosure relates to a processor-readable medium including instructions for causing a computer or other processing element to: compute a statistic of a received positioning signal, wherein the received positioning signal includes a direct path signal component and one or more multipath signal components, compute an estimated covariance of the received positioning signal, determine, if the statistic is within a first range, an estimated time of arrival of the direct path signal using a first method, determine, if the statistic is within a second range, an estimated time of arrival of the direct path signal using a second method, and determine, based at least in part on the estimated time of arrival, a distance estimate between the transmitter and the receiver.
  • the disclosure relates to a positioning system receiver.
  • the receiver may include, for example, an RF module for receiving a positioning signal including a direct path signal component and one or more multipath signal components, a processing module configured for computing a statistic of the received positioning signal, computing an estimated covariance of the received positioning signal, determining, if the statistic is within a first range, an estimated time of arrival of the direct path signal using a first method, determining, if the statistic is within a second range, an estimated time of arrival of the direct path signal using a second method, and determining, based at least in part on the estimated time of arrival, a distance estimate between the transmitter and the receiver.
  • the receiver may further include an output module for providing the distance estimate as an output.
  • the output may be provided as an audible output or visual display.
  • the output may be sent/transmitted from the receiver to a wired or wireless communications network, such as a cellular or data network.
  • the communications network may be an emergency response network.
  • the output may be sent to another device or system on the communications network.
  • the output may be provided on an audio output or visual display of the receiver.
  • the disclosure relates to a method of determining location information in a receiver and/or storing the information and/or providing the information to a user or other electronic computing system or device.
  • the method may include, for example, receiving a positioning signal from a transmitter.
  • the positioning signal may include a direct path signal and one or more multipath signals.
  • the direct path signal may be stronger than the multipath signal in some environments. Alternately, one or more of the multipath signals may be stronger than the direct path signal.
  • the method may further include determining an estimated covariance of the received positioning signal, and determining a set of eigenvalues of the estimated covariance.
  • the method may further include determining a set of potential times of arrival of the positioning signal components, and selecting a first time of arrival value from the set of potential times of arrival.
  • the method may further include determining the value of a quality metric based on information associated with the selected first time of arrival.
  • the method may further include removing the selected first time of arrival from the set of potential times of arrival if the quality metric value is below a predefined threshold to generate a adjusted set of potential times of arrival and repeating the selecting, determining a value of a quality metric, and removing additional selected first times of arrival until the quality metric value is above the predefined threshold.
  • the method may further include determining a distance between the transmitter and receiver from the adjusted set of potential times of arrival.
  • the quality metric may, for example, include a measure of the time of arrival difference between the selected first time of arrival and an estimate of the time of arrival of the positioning signal.
  • the measure may be based at least in part upon the location of a time domain cross-correlation peak.
  • the method may include implementation of a Likelihood MUSIC algorithm to determine a set of early arrival peaks from the pseudospectrum.
  • the quality metric may be based on a decision as to whether or not the correlation peak associated with the selected first time of arrival falls within a signal power versus delay mask, relative to the location and power of the strongest correlation peak.
  • the quality metric may include a measure of the strength of a signal associated with the selected first time of arrival relative to a measure of noise.
  • the first method and second method may, for example, be chosen from a set of at least two different methods.
  • the methods may be chosen is based at least in part upon a computation of a statistic associated with the received positioning signal.
  • the statistic may be a measure of the signal-to-noise ratio of the positioning signal.
  • the method may further include, for example, determining, based in part on the distance estimate, a location of the receiver, and providing the determined location as an output.
  • the output may be sent/transmitted from the receiver to a wired or wireless communications network, such as a cellular or data network.
  • the communications network may be an emergency response network.
  • the output may be sent to another device or system on the communications network.
  • the output may be provided on an audio output or visual display of the receiver.
  • the location of the receiver may be determined based on a triangulation procedure utilizing the distance estimate determined from the transmitter and additional distance estimates determined from two or more additional transmitters.
  • the disclosure relates to a processor-readable medium including instructions for causing a computer to: determine an estimated covariance of a received positioning signal, wherein the received positioning signal includes a direct path signal component and one or more multipath signal components, determine a set of eigenvalues of the estimated covariance, determine a set of potential times of arrival of the positioning signal components, select a first time of arrival value from the set of potential times of arrival, determine a quality metric value based on information associated with the selected first time of arrival, remove the selected first time of arrival from the set of potential times of arrival if the quality metric value is below a predefined threshold to generate a adjusted set of potential times of arrival, and determine a distance between the transmitter and receiver from the adjusted set of potential times of arrival.
  • the disclosure relates to a positioning system receiver.
  • the receiver may include, for example, an RF module for receiving a positioning signal including a direct path signal component and one or more multipath signal components, and a processing module for: determining an estimated covariance of the received positioning signal, determining a set of eigenvalues of the estimated covariance, determining a set of potential times of arrival of the positioning signal components, selecting a first time of arrival value from the set of potential times of arrival, determining a quality metric value based on information associated with the selected first time of arrival, removing the selected first time of arrival from the set of potential times of arrival if the quality metric value is below a predefined threshold to generate a adjusted set of potential times of arrival, and determining a distance between the transmitter and receiver from the adjusted set of potential times of arrival.
  • exemplary means serving as an example, instance or illustration. Any aspect and/or embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects and/or embodiments.
  • the term “quality metric” refers to one or more measurements that result in a number whose value may be used in a decision making stage.
  • the value of a quality refers to a numeric value that is computed as a function of the measurements. The value may be computed in a complex manner
  • a quality metric may be based upon a “measure”, as in measure of time of arrival difference.
  • Measure means a function, such a function of the time of arrival difference.
  • a measure may be proportional to time of arrival difference, or it may mean proportional to the reciprocal of time of arrival difference, or it may mean a more complex function of the time of arrival difference.
  • WAPS Wide Area Positioning Systems
  • WAPS Wide Area Positioning Systems
  • time of arrival of positioning signals sent from multiple transmitters are measured at a corresponding receiver to determine distances to known transmitter locations, and thereby allow position triangulation.
  • a fundamental limitation on performance in these systems is often imposed by received positioning signals with multipath components (also denoted as multipath signals).
  • Multipath signals are one or more signals present at the receiver from reflections of the originally transmitted signal, which may be amplitude attenuated and/or phase shifted relative to a corresponding direct path signal between the transmitter and receiver. These delayed signals may distort the estimated time of arrival at the receiver in applications where distance is determined based on time of arrival of the direct path signal.
  • a typical WAPS implementation includes multiple towers broadcasting synchronized positioning signals to one or more mobile receivers, such as shown in the example system of FIG. 1 , with the receivers determining distances to each of the transmitters for location determination by triangulation.
  • the towers 110 are terrestrially located, but other systems may use satellite or other non-terrestrial transmitters to implement similar location determination functionality.
  • One or more receivers 120 which may be smart phones, tablet devices, dedicated location devices, or other devices, such as combinations of phones, GPS devices, other radio receivers, and the like, may be used in a typical system.
  • emergency responders may have positioning functionality configured on a cellular phone or other mobile device with receiving and computing capability. Alternately, dedicated mobile locating devices with receiver and processing capability may be used in some applications.
  • Positioning system 100 also referred to herein as a Wide Area Positioning System (WAPS), or “system” for brevity, includes a network of synchronized beacons (also denoted herein as “transmitters”), which are typically terrestrial, as well as user devices (also denoted herein as “receiver units” or “receivers” for brevity) configured to acquire and track signals provided from the beacons and/or other position signaling, such as may be provided by a satellite system such as the Global Positioning System (GPS) and/or other satellite or terrestrially based position systems.
  • GPS Global Positioning System
  • the receivers may optionally include a location computation engine to determine position/location information from signals received from the beacons and/or satellite systems, and the system 100 may further include a server system in communication with various other systems, such as the beacons, a network infrastructure, such as the Internet, cellular networks, wide or local area networks, and/or other networks.
  • the server system may include various system-related information and components, such as an index of towers, a billing interface, one or more encryption algorithm processing modules, which may be based on one or more proprietary encryption algorithms, a location computation engine module, and/or other processing modules to facilitate position, motion, and/or location determination for users of the system.
  • the above described transmitters need not be restricted to only transmitting information, but may also have receiving functionality, both in wired and wireless configurations.
  • the transmitters may receive synchronization information from external entities.
  • the above described receivers normally have transmitting functionality, both in wireless and wired configurations.
  • the receivers may transmit information to the transmitters wirelessly.
  • emphasis is placed upon the transmitting functions of the transmitters and the receiving functions of the receivers; however, either or both may be include the alternate functionality in various embodiments.
  • the beacons may be in the form of a plurality of transmitters 110
  • the receiver units may be in the form of one or more user devices 120 , which may be any of a variety of electronic communication devices configured to receive signaling from the transmitters 110 , as well as optionally be configured to receive GPS or other satellite system signaling, cellular signaling, Wi-Fi signaling, Wi-Max signaling, Bluetooth, Ethernet, and/or other data or information signaling as is known or developed in the art.
  • the receiver units 120 may be in the form of a cellular or smart phone, a tablet device, a PDA, a notebook or other computer system, and/or similar or equivalent devices.
  • the receiver unit may be a standalone location/positioning device configured solely or primarily to receive signals from the transmitters 110 and determine location/position based at least in part on the received signals.
  • receiver units 120 may also be denoted herein as “User Equipment” (UEs), handsets, smart phones, tablets, and/or simply as a “receiver.”
  • FIG. 2 described subsequently herein, illustrates a block diagram of details of an embodiment of a receiver unit architecture as may be used in various embodiments.
  • the transmitters 110 are configured to send transmitter output signals to multiple receiver units 120 (a single receiver unit 120 is shown in FIG. 1 for simplicity, however, a typical system will be configured to support many receiver units within a defined coverage area) via communication links 113 as shown.
  • the transmitted signals may result in multiple signals being received at the receivers including both direct path signals and one or more multipath signals.
  • the transmitters 110 may also be connected to a server system 130 via communication links 133 , and/or may have other communication connections (not shown) to a network infrastructure 170 , such as via wired connections such as Ethernet, USB, and the like, and/or wireless connections such as cellular data connections, Wi-Fi, Wi-Max, or other wireless connections.
  • a network infrastructure 170 such as via wired connections such as Ethernet, USB, and the like, and/or wireless connections such as cellular data connections, Wi-Fi, Wi-Max, or other wireless connections.
  • One or more receivers 120 may receive signaling from multiple transmitters 110 via corresponding communication links 113 from each of the transmitters 110 .
  • Signals received via communication links 113 may include both direct path components and multipath components reflected from terrain, buildings, or other surfaces or structures.
  • a receiver 120 may also be configured to receive and/or send other signals, such as, for example, cellular network signals via communication link 163 from a cellular base station (also known as a NodeB, eNB, or base station), Wi-Fi network signals, Pager network signals, or other wired or wireless connection signaling, as well as satellite signaling via satellite communication links 153 , such as from a GPS or other satellite positioning system. While the satellite positioning signaling shown in the exemplary embodiment of FIG. 1 is shown as being provided from GPS system satellites 150 , in other embodiments the signaling may be provided from other satellite systems and/or, in some embodiments, terrestrial-based wired or wireless positioning systems or other data communication systems or positioning systems.
  • other signals such as, for example, cellular network signals via communication link 163 from a cellular base station (also known as a NodeB, eNB, or base station), Wi-Fi network signals, Pager network signals, or other wired or wireless connection signaling, as well as satellite signaling via satellite communication links 153 , such
  • the transmitters 110 of system 100 are configured to operate in an exclusively licensed or shared licensed/unlicensed radio spectrum; however, some embodiments may be implemented to provide signaling in unlicensed shared spectrum.
  • the transmitters 110 may transmit signaling in these various radio bands using novel signaling as is described in co-assigned applications, such as in U.S. patent application Ser. No. 13/535,128, which is incorporated by reference herein.
  • This signaling may be in the form of a proprietary signal configured to provide specific data in a defined format advantageous for location and navigation purposes.
  • the signaling may be structured to be particularly advantageous for operation in obstructed environments, such as where traditional satellite position signaling is attenuated and/or impacted by reflections, multipath, and the like.
  • the signaling may be configured to provide fast acquisition and position determination times to allow for quick location determination upon device power-on or location activation, reduced power consumption, and/or to provide other advantages.
  • WAPS may be combined with other positioning systems to provide enhanced location and position determination.
  • a WAPS system may be used to aid other positioning systems.
  • information determined by receiver units 120 of WAPS systems may be provided via other communication network links 163 , such as cellular, Wi-Fi, Pager, and the like, to report position and location information to a server system or systems 130 , as well as to other networked systems existing on or coupled to network infrastructure 170 .
  • a cellular backhaul link 165 may be used to provide information from receiver units 120 to associated cellular carriers and/or others (not shown) via network infrastructure 170 . This may be used to quickly and accurately locate the position of receiver 120 during an emergency, or may be used to provide location-based services or other functions from cellular carriers or other network users or systems.
  • a positioning system is one that localizes one or more of latitude, longitude, and altitude coordinates, which may also be described or illustrated in terms of one, two, or three dimensional coordinate systems (e.g., x, y, z coordinates, angular coordinates, etc.).
  • the positioning system may also provide time of day information to the various receivers.
  • GPS Global Navigation Satellite Systems
  • GNSS Global Navigation Satellite Systems
  • GLONASS Global Navigation Satellite Systems
  • future positioning systems such as Galileo and Compass/Beidou.
  • other positioning systems such as terrestrially based systems, may be used in addition to or in place of satellite-based positioning systems.
  • Embodiments of WAPS include multiple towers or transmitters, such as multiple transmitters 110 as shown in FIG. 1 , which broadcast WAPS data positioning information, and/or other data or information, in transmitter output signals to the receivers 120 .
  • the positioning signals may be coordinated so as to be synchronized across all transmitters of a particular system or regional coverage area.
  • Transmitters may use a disciplined GPS clock source for timing synchronization.
  • WAPS data positioning transmissions may include dedicated communication channel methodologies (e.g., time, code and/or frequency modulation and multiplexing methods) to facilitate transmission of data required for trilateration, notification to subscriber/group of subscribers, broadcast of messages, general operation of the WAPS network, and/or for other purposed such as are described subsequently herein and/or in the following co-assigned patent applications which are incorporated by reference herein: U.S. Utility patent application Ser. No. 13/412,487, entitled WIDE AREA POSITIONING SYSTEMS, filed on Mar. 5, 2012; U.S. Utility patent Ser. No. 12/557,479 (now U.S. Pat. No. 8,130,141), entitled WIDE AREA POSITIONING SYSTEM, filed Sep.
  • dedicated communication channel methodologies e.g., time, code and/or frequency modulation and multiplexing methods
  • 61/502,272 entitled DATA TRANSMISSION METHODS IN WIDE AREA POSITIONING SYSTEMS (WAPS), filed Jun. 28, 2011; U.S. Provisional Patent Application Ser. No. 61/502,276, entitled CODING IN WIDE AREA POSITIONING SYSTEMS, filed Jun. 28, 2011; and U.S. Provisional Patent Application Ser. No. 61/514,369, entitled CELL ORGANIZATION AND TRANSMISSION SCHEMES IN A WIDE AREA POSITIONING SYSTEM (WAPS), filed Aug. 2, 2011. These application may also be denoted collectively herein as the “incorporated applications.” The various aspect, details, devices, systems, and methods disclosed herein may be combined with the teachings of the incorporated applications in WAPS or other similar systems in various embodiments.
  • the positioning information typically transmitted includes one or more of precision timing sequences and positioning data, where the positioning data includes the location of transmitters and various timing corrections and other related data or information.
  • the data may include additional messages or information such as notification/access control messages for a group of subscribers, general broadcast messages, and/or other data or information related to system operation, users, interfaces with other networks, and other system functions.
  • the positioning data may be provided in a number of ways. For example, the positioning data may be modulated onto a coded timing sequence, added or overlaid over the timing sequence, and/or concatenated with the timing sequence.
  • Data transmission methods and apparatus described herein may be used to provide improved location information throughput for the WAPS.
  • higher order modulation data may be transmitted as a separate portion of information from pseudo-noise (PN) timing, or ranging, data.
  • PN pseudo-noise
  • This may be used to allow improved acquisition speed in systems employing CDMA multiplexing, TDMA multiplexing, or a combination of CDMA/TDMA multiplexing.
  • the disclosure herein is illustrated in terms of wide area positioning systems in which multiple towers broadcast synchronized positioning signals to mobile receivers and, more particularly, using towers that are terrestrial; however, the embodiments are not so limited and other systems within the spirit and scope of the disclosure may also be implemented.
  • a WAPS uses coded modulation sent from a tower or transmitter, such as transmitter 110 , called spread spectrum modulation or pseudo-noise (PN) modulation, to achieve wide bandwidth.
  • the corresponding receiver unit such as receiver or user device 120 , includes one or more modules to receive the transmitted signals and process the received signals using a despreading circuit, such as a matched filter or a series of correlators, for example.
  • a despreading circuit such as a matched filter or a series of correlators, for example.
  • Such a receiver produces a waveform which, ideally, has a strong peak surrounded by lower level energy. The time of arrival of the peak represents the time of arrival of the transmitted signal at the mobile receiver.
  • a WAPS may use binary coded modulation as the spreading method.
  • the WAPS signals of an exemplary embodiment may include two specific types of information: (1) a high speed ranging signal, and (2) location data such as transmitter ID and position, time of day, health, environmental conditions such as pressure data, etc.
  • WAPS may, similar to GPS, transmit location information by modulating a high speed binary pseudorandom ranging signal with a lower rate information source.
  • the disclosures of the incorporated applications describe embodiments of methods and devices that use a pseudorandom ranging signal and a modulating information signal, both of which may utilize higher order modulations, such as quaternary or octonary modulation. These disclosures may be combined with the descriptions herein in various alternate embodiments.
  • the ranging signal is binary phase modulated, and location information is provided in a separate signal using higher order modulation.
  • Conventional systems use a format of a position location signal (e.g., used in a Time Division Multiplexing arrangement) in which each slot transmission comprises a pseudorandom ranging signal followed by various types of location data.
  • a position location signal e.g., used in a Time Division Multiplexing arrangement
  • these conventional systems also include a synchronization, or sync, signal, which may be deleted if the pseudorandom ranging signal is used also as the sync signal.
  • the location data of these conventional systems is binary, which limits throughput. These systems also transmit a large number of binary bits during the interval in which the location data is transmitted.
  • a binary, or quaternary, pseudorandom signal may be transmitted in a particular slot followed by a higher order modulated data signal.
  • one or more location information symbols may be transmitted using differential 16-phase modulation, in order to transmit four bits of information per slot. This represents a four-fold throughput improvement versus the one bit typically transmitted when binary phase modulation is imposed upon the pseudorandom carrier.
  • Other types of modulation of location information may also be utilized, such as 16 QAM, etc.
  • certain error control modulation methods may be used for the higher level modulation, such as the use of Trellis codes. These modulation methods generally reduce error rates.
  • a mobile receiver such as a cellular phone 120 or other received device, may receive multiple delayed “copies” (also referred to herein as multipath components) of a single transmitted signal, such as signal 113 from one of the towers 110 of FIG. 1 , with the multiple signals corresponding to a multiplicity of reflected paths as well as (in many cases) a direct path signal component between each transmitter and the receiver.
  • the delayed signals may be due to reflective surfaces in the operating environment such as buildings or other structures, terrain, and the like.
  • delayed signals may also be attenuated and/or phase shifted, relative to a direct line of sight signal, if one exists. While signal configuration and signaling techniques may be implemented to mitigate these effects, such as described in, for example, co-assigned U.S. patent application Ser. No. 13/535,128, other methods, such as the eigenvalue-based and other methods described subsequently herein, may be used to further mitigate multipath problems.
  • the range of delays of the multipath signal components is typically constrained by geometric constraints of the environment. For example, a delay spread of 1 microsecond corresponds to a maximum differential path length of approximately 300 meters, and a delay spread of 5 microseconds to approximately 1500 meters. Knowledge of the maximum likely delay spread is useful in determining a time range over which a receiver may examine the paths from, and may allow discarding of spurious signals. Maximum delay spread is a function of the environment and parameters such as the spacing of buildings and other structures, terrain, and other characteristics such as attenuating surfaces and the like.
  • Typical WAPS such as those described in co-assigned U.S. patent application Ser. No. 13/535,128, use coded modulation, such as spread spectrum modulation, or pseudonoise (PN) modulation, to achieve wide bandwidth.
  • transmitters such as transmitters 110 of FIG. 1
  • PN pseudonoise
  • the mobile receiver then processes the coded signals with a despreading device, typically a matched filter or a series of correlators.
  • a despreading device typically a matched filter or a series of correlators.
  • Such a receiver produces an output signal waveform which ideally (in the absence of any reflected signals) has a strong peak surrounded by lower level energy, such as example output signal 310 A as shown in FIG. 3A .
  • the time of arrival of the peak (T 1 ) corresponds with the time of arrival of the transmitted signal at the mobile device.
  • Performing operation on a multiplicity of signals from a multiplicity of towers, whose locations are accurately known, allows determination of the mobile's location via trilateration algorithms.
  • three or more towers 110 may send uniquely encoded signals to the receiver 120 , which may then estimate the distance to each tower and triangulate a position from the estimated distances.
  • distance estimation errors due to multipath may introduce triangulation errors, and in some cases, such as described subsequently herein, may cause catastrophic errors in location determination. This can be extremely problematic in applications such as first-response during emergencies and the like.
  • the wideband pseudonoise modulation often takes the form of a high rate binary or quaternary phase shift keyed signal, no such limitation is imposed upon the aspects disclosed herein, and the same or similar concepts may be implemented in other systems.
  • other wideband coding methods such as chirp modulation, orthogonal frequency division multiplexing (OFDM), high rate frequency hopping, etc., may benefit from the processing methods and systems described herein.
  • OFDM orthogonal frequency division multiplexing
  • a despreading module or equivalent hardware and/or software module are utilized at a receiver to produce a waveform having a strong peak (corresponding to the direct path signal), which may be utilized to measure time of arrival, along with possible weaker peaks that correspond to the multipath signals.
  • the direct path signal may be weaker than the other signals, and the receiver preferentially still identifies the direct path signal.
  • the direct and multipath signals may overlap each other significantly as a function of time and the receiver attempts to distinguish these signals from one another and identify the direct path, if possible, such as shown in the example of FIG. 3C .
  • the signal processing methods and systems provided herein also may be applied to non-spread spectrum signals, such as other signals that are pulse like in nature or can be processed at a receiver to provide an output peak corresponding to a signal arrival time.
  • Receiver 200 may include one or more GPS modules 240 for receiving GPS signals and determining location information and/or other data, such as timing data, dilution of precision (DOP) data, or other data or information as may be provided from a GPS or other positioning system, and providing the determined information to processing module 210 and/or other modules of the receiver. It is noted that while receiver 200 is shown in FIG. 2 with a GPS module, other modules for receiving satellite or terrestrial signals and providing similar or equivalent output signals, data, or other information may alternately be used in various embodiments.
  • GPS modules 240 for receiving GPS signals and determining location information and/or other data, such as timing data, dilution of precision (DOP) data, or other data or information as may be provided from a GPS or other positioning system, and providing the determined information to processing module 210 and/or other modules of the receiver. It is noted that while receiver 200 is shown in FIG. 2 with a GPS module, other modules for receiving satellite or terrestrial signals and providing similar or equivalent output signals, data, or other information may alternately be used in various embodiment
  • Receiver 200 may also include one or more cellular modules 250 for sending and receiving data or information via a cellular or other data communications system. Alternately, or in addition, receiver 200 may include communications modules (not shown) for sending and/or receiving data via other wired or wireless communications networks, such as Wi-Fi, Wi-Max, Bluetooth, USB, Ethernet, or other data communication networks.
  • communications modules not shown
  • Receiver 200 may include one or more position/location modules for receiving signals from terrestrial transmitters, such as transmitters 110 as shown in FIG. 1 , and processing the signals to determine position/location information as described subsequently herein, including for performing multipath signal processing as described subsequently with respect to FIGS. 7-13 .
  • Module 260 may be integrated with and/or may share resources such as antennas, RF circuitry, and the like with other modules, such as, for example, GPS module 240 .
  • Position module 260 and GPS module 240 may share some or all radio front end (RFE) components and/or processing elements.
  • Processing module 210 may be integrated with and/or share resources with Position module 260 and/or GPS module 240 to determine position/location information and/or perform other processing functions as described herein.
  • cellular module 250 may share RF and/or processing functionality with RF module 230 and/or processing module 210 .
  • a despreading module 265 may be incorporated in position module 260 and/or processing module 210 in various embodiments, or may be a separate module or part of the RF receiver module 230 .
  • One or more memories 220 may be coupled with processing module 210 to provide storage and retrieval of data and/or to provide storage and retrieval of instructions for execution in the processing module 210 .
  • the instructions may be for performing the various processing methods and functions described subsequently herein, such as for performing multipath signal processing, determining location information or other information based on received transmitter, GPS, cellular, pressure, temperature, and/or other signals or data, or for implementing other processing functions.
  • Receiver 200 may further include one or more environmental sensing modules 270 for sensing or determining conditions associated with the receiver, such as, for example, local pressure, temperature, or other conditions.
  • pressure information may be generated in environmental sensing module 270 and provided to processing module 210 for use in determining location/position information in conjunction with received transmitter, GPS, cellular, or other signals.
  • Receiver 200 may further include various additional user interface modules, such as a user input module 280 , which may be in the form of a keypad, touchscreen display, mouse, or other user interface element. Audio and/or video data or information may be provided on an output module 290 , such as in the form of one or more speakers or other audio transducers, one or more visual displays, such as LCD displays, touchscreens, and/or other user I/O elements as are known or developed in the art. In an exemplary embodiment, output module 290 may be used to visually display determined location/position information based on received transmitter signals. The determined location/position information may also be sent to cellular module 250 to an associated carrier or other entity.
  • a user input module 280 may be in the form of a keypad, touchscreen display, mouse, or other user interface element. Audio and/or video data or information may be provided on an output module 290 , such as in the form of one or more speakers or other audio transducers, one or more visual displays, such as LCD displays, touchscreens, and/or other user I/O
  • a matched filter is used to process a received spread spectrum signal.
  • the matched filter may be implemented in a processing element, such as processing module 210 , or in other receiver modules such as position module 260 , or other modules, such as depreading module 265 .
  • Matched filter implementation methods and signal processing hardware are well known in the art. Assuming use of a matched filter to process a received spread spectrum signal, when multipath is present, the matched filter output produces a series of (possibly) overlapping sharp pulses of varying amplitudes, delays and phases.
  • FIGS. 3A , 3 B and 3 C show example magnitude outputs from such a matched filter.
  • the dotted lines show the true times of arrival of three returns. Note that in FIGS. 3B and 3C the peak locations of the matched filter magnitudes are not coincident with the true times of arrival. In practice both the magnitude and phase (or inphase and quadrature components) from the matched filter are available from which to determine times of arrival.
  • the mobile receiver attempts to estimate the time of arrival of the earliest such pulse from the matched filter.
  • a variety of algorithms may be used for this purpose, such as leading edge location algorithms, MUSIC algorithm, minimum mean square estimation algorithms, etc. Embodiments of the various aspects disclosed herein may be used to improve performance of such receivers.
  • FIGS. 3A and 3B show the magnitudes of pulses exiting the matched filter that are clearly discernible from one another.
  • the location of the first two peaks are not coincident with the true times of arrival of the individual returns, as indicated by the dotted lines.
  • several of these pulses may heavily overlap one another, so that such overlapping pulses are not easily distinguishable from one another by a simple peak finding algorithm.
  • An example of overlapping pulses is illustrated in FIG. 3C , where it is seen that the first two pulses actually merge together to form a single pulse (the dotted lines show the true times of arrival).
  • more powerful methods such as the aforementioned MUSIC algorithm, may be employed to better separate out such overlapping pulses and measure their individual times of arrival.
  • Exemplary embodiments of the methods and apparatus described herein are focused upon the cases of pulses that are heavily overlapped with one another.
  • a similar such system is one in which the transceiver initiates the round trip procedure and the time difference is hence measured at the transceiver. All such embodiments based upon time-of-arrival measurements may benefit from the invention herein; however, for clarity only the forward TOA positioning method is discussed in the following. It will be apparent to one of ordinary skill at the art that similar implementations may also be used in various other systems.
  • the direct path signal and one or more delayed signals should be separated for determining the earlier arrival time for distance estimation.
  • a number of methods have been developed in the art to separate these multiple delayed signals from each other at the receiver. These are sometimes termed “superresolution” algorithms. Many of these methods depend upon an eigenvalue decomposition of an estimated covariance matrix constructed from received sampled data.
  • One aspect of this disclosure is directed to various embodiments of methods for processing received signals to separate the eigenvalues of such a decomposition into those associated with additive noise and those associated with the positioning signals.
  • embodiments may include improved methods for processing received signals to discard spurious estimates of the time of arrival of the earliest signal. The resulting processed information may provide improvement in determining the time of arrival of the earliest received positioning signal, which may be used to improve overall positioning accuracy.
  • sample covariance relates to the following concept.
  • the received signal is processed in some manner to provide a sample vector, say, X, where X is a column vector of dimension M.
  • the processor then wishes to determine the expected value of XX′, which is termed the covariance herein, where the prime denotes the Hermitian conjugate.
  • covariance the expected value of XX′
  • this generally refers to estimated covariance, rather than the actual true covariance, and it should be clear in the context where this is the case.
  • a variety of algorithms may be used to estimate this quantity, as discussed subsequently herein.
  • processing errors in determining first path time of arrival may give rise to potentially catastrophic positioning errors, a characteristic which may not be important in other applications.
  • the location of the first (presumably direct) peak is missed, or greatly in error, as seen to be possible in the examples of FIG. 3B or 3 C, then large errors in time of arrival may also occur.
  • MUSIC Multiple Signal Characterization
  • the data being processed consists of a set of (sampled) signals plus additive independent noise.
  • the covariance of such data consists of a covariance associated with the signal plus a covariance associated with the noise.
  • the overall eigenspace can be separated into orthogonal subspaces associated with the signal and noise.
  • the noise samples are Gaussian and white and hence the (ideal) eigenvalues associated with the noise subspace are equal and small in value.
  • the eigenvalues associated with the signal subspace are typically much larger in value, especially if the signal-to-noise ratio, after the despreader, is large.
  • this functional is simply the set of transmitted signal samples parameterized by delay.
  • the processing is performed in the frequency domain by performing a discrete Fourier transform of the data.
  • the array manifold takes the form of a weighted complex sinusoid with the parameter being frequency, which is directly related to the delay, or time of arrival.
  • the orthogonality of the noise eigenvectors to the array manifold, when the correct parameters are chosen, may be used to determine these parameters, which are easily related to the times of arrival of the various signals.
  • FIGS. 14A and 14B provide examples of pseudospectrum amplitude versus delay.
  • FIG. 14A shows the case in which the first path ( 1410 A) has a larger output amplitude than the other paths and
  • FIG. 14B shows the situation in which the first path ( 1410 B) is smaller.
  • the peaks provided by the pseudospectra may be distinct even if the corresponding peaks in the matched filter output heavily overlap and are not distinguishable (as in FIG. 3C ). Furthermore, the peaks in the pseudospectra often eliminate large time biases that may be present in the peak locations from the matched filter (see FIG. 3B , for example).
  • the noise subspace has dimensionality M-D and the signal subspace dimension D.
  • M-D the required full rank nature of the signal subspace is sometimes a concern in the application of these algorithms.
  • various methods have been derived in constructing the covariance to ensure that this subspace is full rank.
  • the noise being white, there would be M-D eigenvalues of the noise, having similar small values, and D larger signal eigenvalues. Since the number of echoes D is unknown a priori, it is necessary to estimate this number in some fashion, or equivalently the number of noise eigenvalues M-D. This may be done in the processing element 210 and/or position/location module 260 of FIG. 2 , or in other processing elements of the receiver.
  • a number of algorithms are known in the art to estimate the size of the noise subspace, or equivalently the signal subspace. These include the minimum description length (MDL) and Akaike information criteria. The basis of such algorithms is the use of information theoretic criteria and maximum likelihood or maximum a posteriori estimates to choose the best signal model matching observations. Typically, it is assumed that observations are Gaussian distributed and that the noise eigenvalues are fairly similar in value. However, these assumptions do not hold well under a variety of circumstances. In particular, in a typical WAPS a single snapshot of data is typically used to perform the signal separation, rather than an ensemble of snapshots. This typically renders the Gaussian assumption incorrect.
  • the signal subspace dimension estimation processing is considered. In estimating the size of the signal subspace, if the dimension is chosen to be too low a Type 1 error, or a “miss” will result. If the dimension is chosen too high a Type 2 error, or “false alarm” results. If a false alarm occurs, then at least one of the noise eigenvalues, and associated eigenvectors, is considered a signal eigenvalue and eigenvector. This may give rise to identification of a false peak in the pseudospectrum since the procedure may be looking for more true signal peaks than are present. Depending upon the location of this false peak, the result may be an estimate of the time of arrival of this false signal well before that of the earliest true signal.
  • a Type 1 error typically means that a weak early peak may sometimes be missed (e.g., corresponding with a weak first arriving signal as shown in FIG. 3B ), but this often results in a relatively small positioning error, since other valid peaks still exist and are typically close together.
  • the covariance is estimated as the average of X n X n ′, over all n, where X n is assumed to be a column vector and prime means complex (Hermitian) transpose.
  • the snapshots are all identically distributed. For these conditions, when the noise is additive and white it is known that as the number of snapshots averaged (N) gets large, the distribution of the eigenvalues of the noise subspace tend to cluster around a value equal to the noise variance. In this case information theoretic methods for determining the subspace (noise or signal) dimensions work well.
  • FIG. 4 shows a chart 400 of an (estimated) probability density 410 of the eigenvalues for the case in which the snapshots consisted of 20 samples of complex white Gaussian noise of variance 1 (inphase and quadrature components with variance 1). The covariances of 100 successive snapshots were averaged and the eigenvalues were found. This was repeated 10,000 times in order to accumulate enough data (200,000 values) to construct a histogram with 100 bins. The histogram was normalized to provide the probability density as shown in FIG. 4 , and exhibits the clustering centered on an eigenvalue amplitude of 2, which is the mean of the distribution. It may be noted that the maximum eigenvalue was seen to be only about twice the mean for this case.
  • a second method for estimating the covariance utilizes a single snapshot of data and performs averaging using overlapping segments of such data. These are termed “smoothing methods” or “modified smoothing methods” depending upon the segment selection method. Such methods work only when the single snapshot can be modeled as stationary. For time of arrival estimation, converting a time snapshot into a “frequency domain snapshot” by utilizing a discrete Fourier transform (as indicated previously) can allow the construction of a data sequence that is approximately stationary. Hence this smoothing method may be used to estimate the covariance. In this case, however, the distribution of the eigenvalues tends not to be clustered, but instead is often well modeled somewhat as an exponential distribution.
  • FIG. 5 illustrates a graph 500 showing a statistical distribution of eigenvalues for the smoothed estimation case in which the snapshots consisted of 40 samples of complex white Gaussian noise of variance 1 (inphase and quadrature components with variance 1). For each snapshot the covariance was estimated using overlapped segment lengths of size 20 samples and the forward-backward estimation procedure was used.
  • the resulting eigenvalues (size 20) were then saved and this procedure was repeated 10,000 times to gather data to construct a histogram with 100 bins.
  • the estimated mean of the distribution was approximately 2 (consistent with the input data) and overlaid on the plot is an exponential of the form k exp( ⁇ x/2).
  • k should be 1 ⁇ 2.
  • best match was for k approximately 0.11, the difference presumably due to the curves differing at values less than 0.4.
  • the figure illustrates that the tails of the distribution are much larger than those of FIG. 4 . For example there is a 1% probability that the maximum eigenvalue will be four times the mean, a fact that differs greatly from FIG. 4 .
  • a resultant noise eigenvalue may be selected to be signal and may correspond with an arrival time much earlier than the direct path arrival time.
  • a resultant noise eigenvalue may be selected to be signal and may correspond with an arrival time much earlier than the direct path arrival time.
  • the distribution of eigenvalues follows even more closely an exponential distribution, than that shown in FIG. 5 , i.e. there is not the difference that is shown in FIG. 4 below amplitude 0.4. While an occasional catastrophic error may not be significant in some applications, in others, such as in emergency response applications, such an error may be very important.
  • one method for determining noise subspace dimension is to estimate the statistics of the noise eigenvalues and set a threshold relative to this statistic providing a prescribed false alarm rate.
  • this threshold approach consists of initially modeling the statistical distribution of noise eigenvalues, and then using this information together with the measured eigenvalue levels to establish a threshold above which are declared signal eigenvalues. Simulations by NextNav have shown that this approach appears to work quite well to establish a prescribed false alarm rate.
  • a problem with the above approach is that it may often declare a signal eigenvalue as a noise eigenvalue, thus missing the location of an early multipath return. Of course this may be expected, due to the emphasis on low false alarm rate.
  • this approach and more traditional approaches may benefit from yet another method that provides a secondary check on peaks that are determined in the superresolution algorithm. As described previously, such peaks may be spurious and may have resulted from a noise eigenvalue being declared a signal eigenvalue.
  • the time of arrival associated with such a peak may be qualified by other measurements, called quality metrics, to determine if it should be retained or discarded. Such metrics may include additional time of arrival measurements, signal strength, signal to noise ratio, correlation width, etc. A combination of such metrics may be used as qualification.
  • a coarse measure of time of arrival may be obtained by simply determining the location of the peak out of the matched filter associated with the despreader, for the spread spectrum embodiment discussed earlier. If the time of arrival found from the superresolution algorithm, called the “potential” time of arrival, occurs well before this coarse measure, then this potential time of arrival may be discarded as a false alarm, especially if the power associated with potential time of arrival is low enough.
  • a power level may be that determined by the level of the associated eigenvalue, or may simply be the amplitude of the output of the matched filter at the potential time of arrival, relative to the maximum out of the matched filter, or relative to background noise.
  • a more sophisticated approach would be to filter out peaks associated with potential times of arrival if they do not fall within a region that is a complex function of both time of arrival and signal strength.
  • a “signal mask” may be applied to the despreader output to corroborate the existence of an early path at the time indicated by the superresolution algorithm.
  • a thresholding mask may be centered on a strongest peak in a received signal output such that the mask would begin at its lowest signal strength value at the center and attain a value equal to that of the strongest peak at a pre-determined distance away by rising at a pre-determined slope.
  • the mask may have an exponential characteristic, such as shown in FIG. 6 as curve 620 , with a pre-determined exponent value.
  • potential early path signals need to rise above the threshold in order to be considered viable direct path signals.
  • the mask is centered on peak signal value 616 , while signal 612 is masked out because its amplitude is lower than the threshold defined by mask curve 620 .
  • Signal 614 has an amplitude above the mask threshold, so it may be selected as the direct path signal.
  • the mask imposes a lower limit on how strong an early path peak needs to be in the time domain as it occurs further away from the strongest peak.
  • the value of the exponent used in implementations may be selected based on criteria such as simulation testing and/or operation system test data.
  • Durrani “A Comparative Study of Modern Eigenstructure Methods for Bearing Estimation—A New High Performance Approach.”, Proceedings of the 25 th conference on Decision and Control, Athens, Greece, December 1986), which may be used together with the other qualifying methods described above, may help reduce the risk due to an elevated noise floor.
  • This variation serves the purpose of reducing the noise floor of the pseudospectrum by exploiting the fact that the noise belongs to a Gaussian distribution while the signal does not. The net result is that many fewer noise peaks in the modified pseudospectrum are able to pass the threshold test and pose as false early peaks.
  • an objective of various embodiments in accordance with aspects of the disclosure is to ameliorate the effects of false early peaks in applying superresolution algorithms to the multipath problem, that is, the mis-declaration of a noise eigenvalue and corresponding eigenvector as a signal, or the wrongful identification of a noise peak as an early signal peak in the pseudospectrum.
  • amelioration may be done by (1) utilizing secondary checks upon the estimated signal eigenvalues/eigenvectors and/or by (2) using methods other than the information theoretic methods discussed above to determine which eigenvalues are declared noise eigenvalues.
  • a more general object is to mitigate or prevent catastrophic errors that may occur in a variety of superresolution based time of arrival estimation procedures. This may be done by minimizing the occurrence of false peaks, such as is described subsequently.
  • false peaks may be mitigated by determining the noise and signal subspace dimensions by using an appropriate algorithm, such as MDL, and then implementing a superresolution algorithm to estimate the times of arrival of the various signals from this algorithm and then choosing the earliest time of arrival. Once this is done, the location of the peak from the matched filter may be examined in order to determine a coarse estimate of time of arrival. This may be done in various ways.
  • a lower window boundary may be set prior to this coarse estimate, and a determination made as to whether the time of arrival from the superresolution algorithm was within this window. If it occurred prior to the boundary then it may be discarded, and next earliest peak from the superresolution algorithm may be considered. This processing may be continued until a peak is found within this window.
  • the window boundary size may typically be set based upon physical limitations, such as the maximum multipath time spread that is likely to occur.
  • FIG. 7 An embodiment of a process 700 implementing this method is illustrated in FIG. 7 . Process 700 may be implemented in a user device such as device 120 of FIG. 1 , which may be configured as shown in receiver embodiment 200 of FIG. 2 .
  • Process 700 may begin at stage 705 where a positioning signal is received.
  • the positioning signal may include a direct path component and one or more multipath components.
  • an estimated covariance associated with the received positioning signal may be determined.
  • a superresolution algorithm or similar or equivalent algorithm may be implemented to determine a set of arrival times of the components of the received positioning signal components.
  • a first time of arrival (TOA) of the signal components may be determined.
  • TOA time of arrival
  • a cross-correlation of the received signal may be done, and a coarse TOA may be determined at stage 730 from the peak of the received signal cross-correlation.
  • the difference between the first TOA and coarse TOA may be compared to a predetermined threshold value. If the difference is greater than the threshold, the processing may continue to stage 745 , where the first TOA from the set of received signal components is discarded and stage 720 repeated to determine a new first TOA. Alternately, if the difference at stage 740 is less than the threshold value, processing may continue to stage 750 , where the TOA estimate from the first TOA is assigned to be the estimated TOA for further processing. This TOA may subsequently be used to determine a distance from the transmitter to the receiver for further processing, such as for location triangulation based on positioning signals received from other transmitters.
  • a signal power versus delay mask may be derived whose slope is either one pre-determined value or a value derived from a set of pre-determined values stored in a database, and which is centered on the strongest peak at the despreader output. Once this is done, a check may be made to determine which of the candidates for the earliest arriving path satisfy the mask, and then earliest path from the ones that do satisfy the mask may be selected.
  • FIG. 8 An embodiment of a process 800 implementing this method is illustrated in FIG. 8 .
  • Process 800 may be implemented in a user device such as device 120 of FIG. 1 , which may be configured as shown in receiver embodiment 200 of FIG. 2 .
  • Process 800 may begin at stage 805 where a positioning signal is received, which may be similar to process stage 705 of FIG. 7 .
  • the positioning signal may include a direct path component and one or more multipath components.
  • an estimated covariance associated with the received positioning signal may be determined, which may be similar to process stage 710 .
  • a superresolution algorithm or similar or equivalent algorithm may be implemented to determine a set of arrival times of the components of the received positioning signal components, which may be similar to process stage 715 .
  • a first time of arrival (TOA) of the signal components may be determined, which may be similar to process stage 720 .
  • TOA time of arrival
  • a cross-correlation may be performed on the received signal and a coarse TOA may be determined from peaks of the cross-correlation, which may be done similarly to stages 725 and 730 .
  • a signal mask such as shown in FIG. 6 , may be applied to the peak values, and a decision stage 840 applied to the masked peak values.
  • processing may proceed to stage 845 , where the first TOA estimate is discarded and processing is continued to stage 820 for determination of another first TOA estimate.
  • processing may be continued to stage 850 , where the TOA estimate from the earliest TOA satisfying the mask criteria is assigned to be the estimated TOA for further processing.
  • This TOA value may subsequently be used to determine a distance from the transmitter to the receiver for further processing, such as for location triangulation based on positioning signals received from other transmitters.
  • an algorithm based upon the statistics of the noise eigenvalues may be used to establish a detection threshold.
  • This threshold may be set to achieve a prescribed false alarm rate. All eigenvalues below this threshold may be declared noise eigenvalues. This method may be used to mitigate, and potentially largely eliminate, catastrophic errors if the false alarm rate is set sufficiently high.
  • approach C a combination of the previously described approaches A and B may be implemented, depending upon estimated signal strength. For example below a prescribed SNR the MDL algorithm may be used, whereas above a prescribed SNR the approach in B may be used, or vice versa. In either case the secondary checks described above may be used. Simulations by assignee NextNav have shown that a combination of algorithm may work better than either alone.
  • the previously described methods may also be supplemented by Likelihood MUSIC to further avoid spurious noise peaks in the pseudospectrum from being designated as potential early arrival signal peaks.
  • FIG. 9 illustrates an embodiment of a process 900 as may be used in a user device such as user device 120 of FIG. 1 .
  • Process 900 may be implemented in a receiver architecture such as shown in FIG. 2 .
  • a positioning signal may be received, including a direct path signal component and one or more multipath signal components.
  • an estimated covariance of the received signal may be determined, and the value of a metric associated with the signal determined at stage 915 .
  • the metric value may be compared to a threshold.
  • a second method may be used to compute times of arrival of the various components.
  • a first method may be used to computer times of arrival paths.
  • the paths may be qualified with a statistic, such as times relative to a coarse time of arrival, and at stage 960 the earliest path to meet the quality condition may be selected as the direct path TOA. This TOA may then be used for distance and/or location determination of the receiver.
  • FIG. 10 illustrates an embodiment of an alternate process 1000 as may be used in a user device such as user device 120 of FIG. 1 .
  • Process 1000 may likewise be implemented in a receiver architecture such as shown in FIG. 2 .
  • a positioning signal may be received, including a direct path signal component and one or more multipath signal components.
  • an estimated covariance of the received signal may be determined, and a metric value associated with the signal determined at stage 1015 .
  • the value of a metric may be compared to a threshold. If the metric value is below the threshold processing may continue to stage 1030 where a second method may be used to compute times of arrival of the various components. Alternately, if the metric value is above the threshold at stage 1020 , a first method may be used to computer times of arrival paths.
  • spurious noise peaks may be filtered out using a Likelihood MUSIC algorithm or similar or equivalent algorithm.
  • a signal mask may then be applied to the remaining peaks as a secondary check, and at stage 1070 the earliest peak meeting the mask criteria may be selected for the direct path TOA. This TOA may then be used for distance and/or location determination of the receiver.
  • FIG. 11 illustrates details of an embodiment of a process 1100 for determining a distance estimate from a transmitter to a receiver in a positioning system such as the WAPS system shown in FIG. 1 .
  • Process 1100 may begin at stage 1110 , where a positioning signal is received from a transmitter.
  • the received positioning signal may include a direct path signal component as well as one or more multipath signal components.
  • the direct path signal component may be stronger than the multipath signal components in some environments. Alternately, one or more of the multipath signal components may be stronger than the direct path signal component.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • estimated covariance of the received positioning signal may be computed.
  • a set of eigenvalues of the estimated covariance may be determined, and at stage 1140 a statistical distribution of the eigenvalues may be estimated.
  • the set of eigenvalues may be separated, such as based on a threshold, into a first subset of eigenvalues corresponding to a transmitted signal including the direct path signal component and the multipath signal components, and a second set of eigenvalues corresponding to noise components.
  • the threshold may be based at least in part on the estimated statistical distribution.
  • the first set of eigenvalues may be used to estimate a time of arrival of the direct path signal component, and a distance estimate between the transmitter and receiver may be implemented based at least in part on the first subset of eigenvalues and associated eigenvectors
  • a location of the receiver may be determined, such as by using the distance estimate along with additional distance estimates or other information, in a triangulation calculation or other geometric location calculation.
  • One eigenvalue And associated eigenvector of the first set of eigenvalues may be selected as corresponding to the direct path signal component, which may be used to determine the estimated time of arrival.
  • the distance estimate may be determined based at least in part on the estimated time of arrival.
  • the process 1100 may further include determining, based in part on the distance estimate, a location of the receiver.
  • the method may further include providing the determined location as an output.
  • the output may be sent/transmitted from the receiver to a wired or wireless communications network, such as a cellular or data network.
  • the communications network may be an emergency response network.
  • the output may be sent to another device or system on the communications network.
  • the output may be provided on an audio output or visual display of the receiver.
  • FIG. 12 illustrates details of an embodiment of a process 1200 for determining a distance estimate from a transmitter to a receiver in a positioning system such as the WAPS system shown in FIG. 1 .
  • Process 1200 may begin at stage 1210 , where a positioning signal is received from a transmitter.
  • the positioning signal may include a direct path signal component and one or more multipath signal components.
  • the direct path signal component may be stronger than the multipath signal components in some environments. Alternately, one or more of the multipath signal components may be stronger than the direct path signal component.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • a statistic of the received positioning signal may be determined.
  • an estimated covariance of the received positioning signal may be determined, and at stage 1240 an estimate of the statistical distribution of eigenvalues may be determined.
  • an estimated time of arrival of the direct path signal may be determined using a first method.
  • an estimated time of arrival of the direct path signal may be determined using a second method. The second method may be different from the first method.
  • a distance estimate between the transmitter and receiver may be determined based on the estimated TOA from stage 1250 or stage 1260 .
  • a location of the receiver may be determined, such as by using the distance estimate along with additional distance estimates or other information, in a triangulation calculation or other geometric location calculation.
  • the first method may, for example, include use of an information theoretic criterion for estimating a number of eigenvalues associated with a signal subspace of the estimated covariance.
  • the estimated time of arrival may be based on a selected one of the eigenvalues.
  • the first or second method may include use of a statistic of the estimated covariance to estimate a number of eigenvalues in a positioning signal subspace of the estimated covariance, wherein the estimated time of arrival is based on a selected one of the eigenvalues.
  • the statistic may be a measure of a signal-to-noise ratio of the received positioning signal.
  • the process 1200 may further include determining, based in part on the distance estimate, a location of the receiver, and providing the determined location as an output.
  • the output may be sent/transmitted from the receiver to a wired or wireless communications network, such as a cellular or data network.
  • the communications network may be an emergency response network.
  • the output may be sent to another device or system on the communications network.
  • the output may be provided on an audio output or visual display of the receiver.
  • FIG. 13 illustrates details of an embodiment of a process 1300 for determining a distance estimate from a transmitter to a receiver in a positioning system such as the WAPS system shown in FIG. 1 .
  • Process 1300 may begin at stage 1310 , where a positioning signal is received from a transmitter.
  • the positioning signal may include a direct path signal and one or more multipath signals.
  • the direct path signal may be stronger than the multipath signal in some environments. Alternately, one or more of the multipath signals may be stronger than the direct path signal.
  • the direct and multipath components may heavily overlap one another in times of arrival at a receiver.
  • an estimated covariance of the received positioning signal may be determined, and at stage 1330 a set of eigenvalues of the estimated covariance may be determined.
  • a set of potential times of arrival of the positioning signal components and at stage 1350 a first time of arrival value from the set of potential times of arrival may be selected.
  • a quality metric value which may be based on information associated with the selected first time of arrival, may be selected.
  • the selected first time of arrival from the set of potential times of arrival may be removed from the set if the quality metric value is below a predefined threshold, and an adjusted set of potential times of arrival may be generated without the removed value.
  • the processing may include repeating the selecting, determining a value of a quality metric, and removing additional selected first times of arrival until the quality metric value of a selected first TOA value from the set is above the predefined threshold.
  • a distance between the transmitter and receiver may be determined from the adjusted set of potential times of arrival, and at stage 1390 , a location of the receiver may be determined, such as by using the distance estimate along with additional distance estimates or other information, in a triangulation calculation or other geometric location calculation.
  • the quality metric may, for example, include a measure of the time of arrival difference between the selected first time of arrival and an estimate of the time of arrival of the positioning signal.
  • the measure may be based at least in part upon the location of a time domain cross-correlation peak.
  • the method may include implementation of a Likelihood MUSIC algorithm to determine a set of early arrival peaks from the pseudospectrum.
  • the quality metric may be determined based on a decision as to whether or not the correlation peak associated with the selected first time of arrival falls within a signal power versus delay mask, relative to the location and power of the strongest correlation peak.
  • the quality metric may include a measure of the strength of a signal associated with the selected first time of arrival relative to a measure of noise.
  • the process 1300 may further include, for example, determining, based in part on the distance estimate, a location of the receiver, and providing the determined location as an output.
  • the output may be sent/transmitted from the receiver to a wired or wireless communications network, such as a cellular or data network.
  • the communications network may be an emergency response network.
  • the output may be sent to another device or system on the communications network.
  • the output may be provided on an audio output or visual display of the receiver.
  • the location of the receiver may be determined based on a triangulation of the distance estimate determined from the transmitter and additional distance estimates determined from two or more additional transmitters.
  • WAPS wide area positioning systems
  • position location systems it is also understood herein that this includes distance measurement, or the measurement of the time-of-arrival of a single signal, when such a time-of-arrival is used in some type of position location calculation.
  • methods described herein may be applied to both forward and inverse positioning systems as well as to round trip time measurement systems or other systems using signal propagation times for distance measurement.
  • Communication paths couple the components and include any medium for communicating or transferring files among the components.
  • the communication paths include wireless connections, wired connections, and hybrid wireless/wired connections.
  • the communication paths also include couplings or connections to networks including local area networks (LANs), metropolitan area networks (MANs), wide area networks (WANs), proprietary networks, interoffice or backend networks, and the Internet.
  • LANs local area networks
  • MANs metropolitan area networks
  • WANs wide area networks
  • proprietary networks interoffice or backend networks
  • the Internet and the Internet.
  • the communication paths include removable fixed mediums like 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 electronic mail messages.
  • USB Universal Serial Bus
  • aspects of the systems and methods described herein may be implemented as functionality programmed into any of a variety of circuitry in one or more processing elements or modules, including programmable logic devices (PLDs), such as field programmable gate arrays (FPGAs), programmable array logic (PAL) devices, electrically programmable logic and memory devices and standard cell-based devices, as well as application specific integrated circuits (ASICs).
  • PLDs programmable logic devices
  • FPGAs field programmable gate arrays
  • PAL programmable array logic
  • ASICs application specific integrated circuits
  • microcontrollers with memory such as electronically erasable programmable read only memory (EEPROM)
  • embedded microprocessors firmware, software, etc.
  • aspects of the systems and methods may be embodied in microprocessors having software-based circuit emulation, discrete logic (sequential and combinatorial), custom devices, fuzzy (neural) logic, quantum devices, and hybrids of any of the above device types.
  • the underlying device technologies may be provided in a variety of component types, e.g., metal-oxide semiconductor field-effect transistor (MOSFET) technologies like complementary metal-oxide semiconductor (CMOS), bipolar technologies like emitter-coupled logic (ECL), polymer technologies (e.g., silicon-conjugated polymer and metal-conjugated polymer-metal structures), mixed analog and digital, etc.
  • MOSFET metal-oxide semiconductor field-effect transistor
  • CMOS complementary metal-oxide semiconductor
  • bipolar technologies like emitter-coupled logic (ECL)
  • polymer technologies e.g., silicon-conjugated polymer and metal-conjugated polymer-metal structures
  • mixed analog and digital etc.
  • any system, method, and/or other components disclosed herein may be described using computer aided design tools and expressed (or represented), as data and/or instructions embodied in various computer-readable media, in terms of their behavioral, register transfer, logic component, transistor, layout geometries, and/or other characteristics.
  • Computer-readable media in which such formatted data and/or instructions may be embodied include, but are not limited to, non-volatile storage media in various forms (e.g., optical, magnetic or semiconductor storage media) and carrier waves that may be used to transfer such formatted data and/or instructions through wireless, optical, or wired signaling media or any combination thereof.
  • Examples of transfers of such formatted data and/or instructions by carrier waves include, but are not limited to, transfers (uploads, downloads, e-mail, etc.) over the Internet and/or other computer networks via one or more data transfer protocols (e.g., HTTP, HTTPs, FTP, SMTP, WAP, etc.).
  • data transfer protocols e.g., HTTP, HTTPs, FTP, SMTP, WAP, etc.
  • a processing entity e.g., one or more processors
  • the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in a sense of “including, but not limited to.” Words using the singular or plural number also include the plural or singular number respectively. Additionally, the words “herein,” “hereunder,” “above,” “below,” and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application. When the word “or” is used in reference to a list of two or more items, that word covers all of the following interpretations of the word: any of the items in the list, all of the items in the list and any combination of the items in the list.
  • the functions, methods and processes described may be implemented in whole or in part in hardware, software, firmware, or any combination thereof in one or more processing elements or modules or other elements or modules as described herein. If implemented in software, the functions may be stored on or encoded as one or more instructions or code on a computer-readable medium.
  • Computer-readable media includes computer storage media. Storage media may be any available media that can be accessed by a computer.
  • Such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
  • Disk and disc includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
  • a general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine.
  • a processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
  • a software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
  • An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium.
  • the storage medium may be integral to the processor.
  • the processor and the storage medium may reside in an ASIC.
  • the ASIC may reside in a user terminal.
  • the processor and the storage medium may reside as discrete components in a user terminal.

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