JP7256241B2 - Partially synchronized multilateration/trilateration method and system for position finding using RF - Google Patents

Description

The present embodiments are for radio frequency (RF)-based identification, tracking, and location of objects, including wireless communication and wireless network systems, and RTLS (real-time location services) and LTE-based location services. Regarding the system.

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a benefit of U.S. Provisional Patent Application No. 62/032,371, filed Aug. 1, 2014, entitled PARTIALLY SYNCHRONIZED MULTILATERATION/TRILATERATION METHOD AND SYSTEM FOR POSITIONAL FINDING USING RF. and also in a continuation-in-part of U.S. patent application Ser. No. 61/514,839, filed Aug. 3, 2011, entitled MULTI-PATH MITIGATION IN RANGEFINDING AND TRACKING OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY, MULTI- ＰＡＴＨ ＭＩＴＩＧＡＴＩＯＮ ＩＮ ＲＡＮＧＥＦＩＮＤＩＮＧ ＡＮＤ ＴＲＡＣＫＩＮＧ ＯＢＪＥＣＴＳ ＵＳＩＮＧ ＲＥＤＵＣＥＤ ＡＴＴＥＮＵＡＴＩＯＮ ＲＦ ＴＥＣＨＮＯＬＯＧＹと題される、２０１１年１１月２日に出願された米国仮出願第６１／５５４，９４５号、ＭＵＬＴＩ－ＰＡＴＨ ＭＩＴＩＧＡＴＩＯＮ ＩＮ ＲＡＮＧＥＦＩＮＤＩＮＧ ＡＮＤ ＴＲＡＣＫＩＮＧ ＯＢＪＥＣＴＳ ＵＳＩＮＧ ＲＥＤＵＣＥＤ ＡＴＴＥＮＵＡＴＩＯＮ U.S. Provisional Application No. 61/618,472, filed March 30, 2012, entitled RF TECHNOLOGY, and MULTI-PATH MITIGATION IN RANGE FINDING AND TRACKING OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY, 2012. 35 U.S. Provisional Application No. 61/662,270, filed Jun. 20; S. C. claiming benefit under §119(e), which are hereby incorporated by reference in their entirety.

U.S. patent application Ser. No. 13, filed Jan. 18, 2011, entitled METHODS AND SYSTEM FOR MULTI-PATH MITIGATION IN TRACKING OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY /008,519 (now U.S. Pat. No. 7,969,311, issued Jun. 28, 2011), which U.S. patent application claims METHODS AND SYSTEM FOR REDUCED ATTENUATION IN TRACKING OBJECTS USING. US patent application Ser. No. 12/502,809, filed July 14, 2009, entitled RF TECHNOLOGY (now US Pat. ), which is a continuation-in-part of U.S. patent application Ser. (now U.S. Pat. No. 7,561,048, issued July 14, 2009), which U.S. patent application claims METHOD AND SYSTEM FOR REDUCED ATTENUATION IN TRACKING OBJECTS USING MULTI-BAND RF. 35 U.S. Provisional Patent Application No. 60/597,649, filed Dec. 15, 2005, entitled TECHNOLOGY. S. C. §119(e), which are hereby incorporated by reference in their entireties.

U.S. patent application Ser. 35 U.S. Provisional Application No. 61/103,270, filed Oct. 7, 2008, entitled OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY. S. C. Benefits under §119(e) are also claimed, which are hereby incorporated by reference in their entireties.

RF-based identification and location systems for determination of relative or geographic position of objects are commonly used to track single objects or groups of objects, as well as to track individuals. Conventional place finding systems are used for position determination in open, outdoor environments. RF-based Global Positioning System (GPS)/Global Navigation Satellite System (GNSS) and auxiliary GPS/GNSS are typically used. However, conventional location-finding systems suffer from certain inaccuracies when locating objects in closed (ie, indoor) environments as well as outdoors.

Cellular wireless communication systems provide various methods of locating user equipment (UE) indoors and in environments that are not well suited for GPS. The most accurate methods are positioning techniques based on multilateration/trilateration. For example, LTE (Long Term Evolution) standard Release 9 specifies DL-OTDOA (Downlink Observed Time Difference of Arrival), and Release 11 specifies multi-sided It defines the U-TDOA (Uplink Time Difference of Arrival) technique, which is the derivative of the survey/trilateration method.

A fundamental requirement for multilateration/trilateration-based systems is perfect and precise time synchronization of the system to a single common reference time, as time synchronization errors affect location accuracy. In cellular networks, DL-OTDOA and U-TDOA localization methods also require that transmissions from multiple antennas are time-synchronized in the case of DL-OTDOA, or multiple receivers in the case of U-TDOA. are time-synchronized.

U.S. Pat. No. 7,561,048 U.S. Pat. No. 5,525,967 U.S. Pat. No. 7,872,583 U.S. Patent Application Publication No. 2008/0285505 International Publication 2010/104436 U.S. Patent Application Publication No. 2003/008156 U.S. Pat. No. 7,167,456 U.S. Patent Application Publication No. 2010/0091826A1 U.S. Patent Application Publication No. 2011/0124347A1 U.S. Pat. No. 7,969,311 U.S. Pat. No. 8,305,215 U.S. Nonprovisional Application No. 13/566,993

Ray H. Hashemi, William G.; Bradley et al., MRI: the basics, 2003 Dan Dobkin, "Indoor Propagation and Wavelength", WJ Communications, V1.4 7/10/02 Kei Sakaguchi et al. , "Influence of the Model Order Estimation Error in the ESPRIT Based High Resolution Techniques" Jakub Marek Borkowski, "Performance of Cell ID + RTT Hybrid Positioning Method for UMTS" Jim Zyren, "Overview of the 3GPP Long Term Evolution Physical Layer", white paper Tsung-Han Lin, et al. , "Microscopic Examination of an RSSI-Signature-Based Indoor Localization System" Gunter Seeber, "Satellite Geodesy", 2003

LTE specifications Release 9 and Release 11 do not specify the accuracy of time synchronization for location purposes, leaving this up to the wireless/cellular service provider. On the other hand, these standards impose limits on the accuracy of ranging. For example, when using a ranging signal bandwidth of 10 MHz, the requirement is 67% reliability at 50 meters for DL-OTDOA and 67% reliability at 100 meters for U-TDOA. be.

The limitations described above are the result of a combination of ranging measurement errors and errors caused by lack of fine synchronization, eg time synchronization errors. From the relevant LTE test specification (3GPP TS36.133 Version 10.1.0 Release 10) and other documents, it is possible to estimate the time synchronization error assuming that the synchronization error is uniformly distributed. . One such estimate would be 200ns (100ns peak to peak). Note that Voice over LTE (VoLTE) functionality also requires cellular network synchronization down to 150 ns (75 ns peak-to-peak), assuming evenly distributed synchronization errors. . Therefore, it is assumed hereinafter that the time synchronization accuracy of the LTE network is within 150 ns.

With respect to remote location accuracy, FCC Directive NG911 defines location accuracy requirements of 50 meters and 100 meters. However, for the location-based services (LBS) market, indoor location requirements are much more stringent, with 67% reliability at 3 meters. As such, the ranging and localization error caused by a 150 ns time synchronization error (43 ns standard deviation) is much larger than a 3 meter ranging error (10 ns standard deviation).

While time synchronization of cellular networks may be sufficient to meet the mandatory FCC NG E911 emergency location requirements, this synchronization accuracy may compromise LBS or RTLS system users who require significantly more accurate location location. does not meet the needs of Therefore, there is a need in the art to mitigate positioning errors caused by lack of precise time synchronization for cellular/wireless networks for the purpose of supporting LBS and RTLS.

The present disclosure includes a real-time location service (RTLS) system that substantially obviates one or more of the shortcomings associated with existing systems for radio frequency (RF)-based identification, tracking, and localization of objects. It relates to a method and system for The method and system can use receivers and/or transmitters that are partially (in time) synchronized. According to an embodiment, RF-based tracking and location is implemented in cellular networks, but can be implemented in any wireless system and RTLS environment. The proposed system may use software-implemented digital signal processing and software-defined radio technology (SDR). Digital signal processing (DSP) may be used as well.

While one approach described herein utilizes clusters of receivers and/or transmitters that are precisely time-synchronized within each cluster, intra-cluster time synchronization can be rather inaccurate. or may not be required at all. The present embodiments may be used in all wireless systems/networks and may include simplex, half-duplex, and full-duplex modes of operation. The embodiments described below operate with wireless networks that utilize various modulation types, including OFDM modulation and/or derivatives thereof. Therefore, the embodiments described below operate with LTE networks and can be applied to other wireless systems/networks.

As described in one embodiment, RF-based tracking and location implemented on 3GPP LTE cellular networks greatly benefits from precisely (time) synchronized receiver and/or transmitter clusters. receive. The proposed system can use digital signal processing implemented in software and/or hardware.

Additional features and advantages of the embodiments are defined in the ensuing description, will be apparent in part from that description, or may be learned by practice of the embodiments. The advantages of the embodiments will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the embodiments as claimed. understood.

4 illustrates narrow bandwidth ranging signal frequency components, in accordance with an embodiment; 4 illustrates narrow bandwidth ranging signal frequency components, in accordance with an embodiment; 4 illustrates exemplary wide bandwidth ranging signal frequency components; 1 illustrates a block diagram of master and slave units of an RF mobile tracking and location system, according to an embodiment. FIG. 1 illustrates a block diagram of master and slave units of an RF mobile tracking and location system, according to an embodiment. FIG. 1 illustrates a block diagram of master and slave units of an RF mobile tracking and location system, according to an embodiment. FIG. 1 illustrates an embodiment of a synthesized wideband baseband ranging signal; FIG. 1 illustrates removal of a signal precursor by cancellation, according to an embodiment. FIG. FIG. 10 illustrates preceding wave cancellation with fewer carriers, according to an embodiment; FIG. 4 illustrates an embodiment of a one-way transfer function phase; 1 illustrates an embodiment of a localization method; 4 illustrates an LTE reference signal mapping; An embodiment of the enhanced Cell-ID+RTT location technique is illustrated. 1 illustrates an embodiment of an OTDOA location technique; 1 illustrates the operation of a Time Observation Unit (TMO) installed at an operator's eNB equipment, according to an embodiment; 1 illustrates an embodiment of a wireless network locating equipment diagram. 1 illustrates an embodiment of a wireless network location downlink ecosystem for enterprise applications; 1 illustrates an embodiment of a wireless network location downlink ecosystem for network-wide applications. 1 illustrates an embodiment of a wireless network location uplink ecosystem for enterprise applications; 1 illustrates an embodiment of a wireless network location uplink ecosystem for network-wide applications. 1 illustrates an embodiment of a UL-TDOA environment that may include one or more DAS and/or femto/small cell antennas; 18 illustrates an embodiment of a UL-TDOA similar to that of FIG. 18 that may include one or more cell towers that may be used in place of DAS base stations and/or femto/small cells. 1 illustrates an embodiment of cell level localization. FIG. 11 illustrates an embodiment of serving cell and sector ID location; FIG. An embodiment of E-CID plus AoA localization is illustrated. 1 illustrates an embodiment of AoA localization. 1 illustrates an embodiment of TDOA using wide open and close distances between receive antennas. An embodiment of a three sector deployment is illustrated. 4 illustrates an embodiment of antenna port mapping; 1 illustrates an embodiment of the LTE Release 11U-TDOA location technique. 1 illustrates an embodiment of a high-level block diagram of a multi-channel location management unit (LMU); 1 illustrates an embodiment of a DL-OTDOA technique in a wireless/cellular network with a location server; 1 illustrates an embodiment of a U-TDOA technique in a wireless/cellular network with a location server; 1 illustrates an embodiment of a depiction of a rackmount enclosure. 1 illustrates an embodiment of a high-level block diagram of multiple single-channel LMUs clustered within a rackmount enclosure. 1 illustrates an embodiment of a high-level block diagram of multiple small cells with integrated LMUs clustered in a rackmount enclosure (one-to-one antenna connection/mapping); FIG. 1 illustrates an embodiment of a high-level block diagram of an integrated LMU and DAS; 1 illustrates an embodiment of a high-level block diagram of an integrated LMU and WiFi infrastructure;

The accompanying drawings, which are included to provide a further understanding of the embodiments, and are incorporated in and constitute a part of this specification, illustrate the embodiments and, together with the description, serve to explain the principles of the embodiments. .

Reference will now be made in detail to preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings.

The present embodiments relate to methods and systems for RF-based identification, tracking, and localization of objects, including RTLS. According to one embodiment, the method and system utilize narrow bandwidth ranging signals. Embodiments operate in the VHF band, but can also be used in the HF, LF, and VLF bands, as well as the UHF band and higher. It utilizes multipath mitigation processors. The use of multipath mitigation processors increases the tracking and location accuracy achieved by the system.

Embodiments include a small, highly portable base unit that allows users to track, locate, and monitor multiple people and objects. Each unit has its own ID. Each unit broadcasts an RF signal with its ID and each unit can transmit back a return signal, which can include its ID as well as voice, data and additional information. Each unit processes the signals returned from the other units and continuously determines their relative and/or actual locations depending on triangulation or trilateration and/or other methods used. to decide. Preferred embodiments can also be easily integrated with products such as GPS devices, smart phones, two-way radios, and PDAs, for example. The resulting product has all the functionality of a standalone device while leveraging existing displays, sensors (such as altimeters, GPS, accelerometers, and compasses), and processing power of its host. For example, a GPS device using the device technology described herein can not only provide the user's location on a map, but can also map the locations of other members of the group.

The size of a preferred embodiment based on an FPGA implementation is approximately 2×4×1 inch to 2×2×0.5 inch, or smaller as integrated circuit technology improves. Depending on the frequency used, the antenna is either integrated into the device or protrudes from the device housing. An ASIC (Application Specific Integrated Circuit) based version of the device can incorporate most of the functionality of the FPGA and other electronic components within a unit or tag. ASIC-based stand-alone products result in device sizes of 1 x 0.5 x 0.5 inches or less. Antenna size is determined by the frequency used and portions of the antenna may be integrated into the housing. ASIC-based embodiments are designed to be integrated into products and can only consist of chipsets. There should be no substantial physical size difference between master or tag units.

Devices can use standard system components (off-the-shelf components) that operate in multiple frequency ranges (bands) for the processing of multipath mitigation algorithms. Software for digital signal processing and software defined wireless communication can be used. Signal processing software combined with minimal hardware allows the construction of wireless communications that transmit and receive waveforms defined by software.

WO 2005/010001 discloses a narrow bandwidth ranging signal system whereby the narrow bandwidth ranging signal, for example, is only a few kilohertz (although some of the low bandwidth channels may extend to tens of kilohertz). It is designed to accommodate low-bandwidth channels with a voice channel that is as wide as . This is in contrast to conventional location-finding systems that use channels ranging from hundreds of kilohertz to tens of megahertz wide.

The advantages of this narrow bandwidth ranging signal system are as follows. 1) At low operating frequencies/bands, the ranging signal bandwidth of conventional location-finding systems exceeds the carrier (operating) frequency value. Therefore, such systems cannot be deployed in LF/VLF and other lower frequency bands, including HF. Unlike conventional location-finding systems, the narrow bandwidth ranging signal system described in US Pat. Can be deployed on the back. 2) At the lower end of the RF spectrum (some VLF, LF, HF, and VHF bands), for example, up to the UHF band, the FCC severely limits the allowable channel bandwidth (12-25 kHz), which is Conventional location-finding systems cannot be used because they render the ranging signal unusable. Unlike conventional location-finding systems, the ranging signal bandwidth of narrow-band ranging signal systems is fully compliant with FCC regulations and other international spectrum regulatory agencies. 3) Independent of the operating frequency/band, it is well known that narrow-bandwidth signals have an inherently higher SNR (signal-to-noise ratio) compared to wide-bandwidth signals (see Non-Patent Document 1). ). This increases the operating range of the narrow bandwidth ranging signal location system, independent of the frequencies/bands in which it operates, including the UHF band.

Therefore, unlike conventional location-finding systems, narrow-bandwidth ranging signal location-finding systems can be used in the RF spectrum, for example, down to the LF/VLF bands, VHF and lower frequency bands, where multipath phenomena are less pronounced. can be deployed on the lower end of the At the same time, narrow bandwidth ranging location systems can also be deployed on the UHF band and beyond to improve ranging signal SNR and consequently increase the operating range of the location system.

It is desirable to operate on the VLF/LF bands to minimize multipath, eg, RF energy reflections. However, at these frequencies, the efficiency of portable/mobile antennas is very low (below about 0.1% due to the small antenna length (size) relative to the RF wavelength). In addition, at these low frequencies the noise levels from natural and man-made sources are considerably higher than on high frequencies/bands, eg VHF. Together, these two phenomena can limit the applicability of a location-finding system, eg, its operating range and/or mobility/portability. Therefore, for certain applications where operating range and/or mobility/portability are very important, higher RF frequencies/bands such as HF, VHF, UHF, and UWB may be used.

In the VHF and UHF bands, noise levels from natural and man-made sources are significantly lower than in the VLF, LF, and HF bands, and at VHF and HF frequencies, multipath phenomena (e.g., RF energy reflections) and less severe than at higher frequencies. Also, at VHF the antenna efficiency is significantly better than at HF and lower frequencies, and at VHF the RF penetration capability is much better than at UHF. Therefore, the VHF band offers a good compromise for mobile/portable applications. On the other hand, in some special cases, eg GPS, where VHF frequencies (or lower frequencies) cannot penetrate the ionosphere (or are deflected/refracted), UHF may be a good option. However, in any case (and all cases/applications), a narrow bandwidth ranging signal system will be advantageous over a conventional wide bandwidth ranging signal location system.

The actual application(s) will determine the exact technical specifications (eg, power, emissions, bandwidth, operating frequency/band, etc.). Narrow bandwidth ranging allows users to receive licenses or exemptions from licenses, or use unlicensed bands as defined by the FCC. Because narrowband ranging allows operation over many different bandwidths/frequencies, including the most stringent narrowbands specified by the FCC: 6.25 kHz, 11.25 kHz, 12.5 kHz, 25 kHz, and 50 kHz. allow and comply with the corresponding technical requirements for the appropriate section. As a result, multiple FCC sections and exemptions within such sections are applicable. The major applicable FCC regulations are 47 CFR Part 90 - Private Land Mobile Radio Services, 47 CFR Part 94 personal Radio Services, 47 CFR Part 15 - Radio Frequency Devices. (By comparison, wideband signals in this context range from a few hundred KHz up to 10-20 MHz.)

Typically, for Part 90 and Part 94, VHF implementations allow users to operate devices up to 100 mW under certain exemptions (low power wireless communication services being one example). For certain applications, the permissible transmitted power in the VHF band is 2-5 Watts. For 900 MHz (UHF band) it is 1 W. Over the 160 kHz-190 kHz frequency (LF band), the permissible transmitted power is 1 Watt.

Narrowband ranging can comply with many, if not all, of the different spectral allowances and allows for accurate ranging while still complying with the most stringent regulatory requirements. This is true not only for the FCC, but also for other international bodies that regulate spectrum usage throughout the world, including Europe, Japan, and South Korea.

Below is a list of common frequencies used, with typical power usage and distance, that the tag can communicate with another reader in a real-world environment (see Non-Patent Document 2). reference).

――――――――――――――――――――――――――――――――――――
915MHz 100mW 150ft 2.4GHz 100mW 100ft 5.6GHz 100mW 75ft―――――――――――――――――――――――――――――――――――― ---

The proposed system operates at VHF frequencies and utilizes proprietary methods for transmitting and processing RF signals. More specifically, it uses DSP techniques and software-defined radio (SDR) to overcome the limitation of narrow bandwidth requirements at VHF frequencies.

Operation at lower (VHF) frequencies reduces scattering and provides much better wall penetration. The net result is an increase of about ten times over the range of frequencies commonly used. For example, compare the measured range of the prototype to that of the RFID technologies listed above.

――――――――――――――――――――――――――――――――――――
216MHz 100mW 700ft ――――――――――――――――――――――――――――――――――――

Employing narrowband ranging techniques would significantly increase the range of commonly used frequencies, and with typical power usage and distance, tag communication range would exceed that of another reader in a real-world environment. be able to communicate with

――――――――――――――――――――――――――――――――――――
to 915MHz 100mW 150ft 500ft 2.4GHz 100mW 100ft 450ft 5.6Ghz 100mW 75ft 400ft ――――――――――

Battery consumption is a function of design, transmitted power, and device duty cycle, eg, the time interval between two consecutive distance (location) measurements. In many applications, the duty cycle is large, 10X-1000X. For applications with a large duty cycle, eg 100X, the FPGA version delivering 100mW of power has an on-time of about 3 weeks. The ASIC-based version is expected to increase run time by a factor of ten. Also, ASICs inherently have lower noise levels. Therefore, the ASIC-based version can also increase the operating range by about 40%.

Those skilled in the art will recognize that embodiments significantly increase location accuracy in RF hostile environments (e.g., buildings, urban corridors, etc.) without compromising the long operating range of the system.

Typically, tracking and locating systems utilize a track-locate-navigate method. These methods include time of arrival (TOA), time difference of arrival (DTOA), and a combination of TOA and DTOA. Time of arrival (TOA) as a distance measurement technique is generally described in US Pat. TOA/DTOA-based systems measure the Direct-Line-Of-Site (DLOS) time-of-flight, eg, time delay, of RF ranging signals, which is then converted to range.

In the case of RF reflections (eg, multipath), multiple copies of the RF ranging signal with different delay times are superimposed on the DLOS RF ranging signal. Track-locate systems using narrow bandwidth ranging signals cannot distinguish between DLOS and reflected signals without multipath mitigation. As a result, these reflected signals induce errors in the estimated ranging signal DLOS time-of-flight, which in turn affects the accuracy of range estimation.

Embodiments advantageously use a multipath mitigation processor to separate the DLOS and reflected signals. Embodiments therefore significantly reduce the error in the estimated ranging signal DLOS time-of-flight. The proposed multipath mitigation method can be used on all RF bands. It can also be used with wide bandwidth ranging signal location systems. Moreover, it can support various modulation/demodulation techniques, including spread spectrum techniques such as DSS (Direct Spread Spectrum) and FH (Frequency Hopping).

Additionally, noise reduction methods may be applied to further improve the accuracy of the method. These noise reduction methods may include, but are not limited to, coherent summing, incoherent summing, matched filtering, time diversity techniques, and the like. The remainder of the multipath interference error can be further reduced by applying post-processing techniques such as maximum likelihood estimation (eg, the Viterbi algorithm), minimum variance estimation (Kalman filter), and the like.

Embodiments may be used in systems using simplex, half-duplex, and full-duplex modes of operation. Full-duplex operation is very demanding in terms of complexity, cost, and logistics for RF transceivers, which limits the system operating range in portable/mobile device implementations. In a half-duplex mode of operation, a reader (often referred to as a "master") and a tag (sometimes also referred to as a "slave" or "target") are capable of controlling any given controlled by a protocol that allows transmission only at times of

Alternating transmission and reception allows a single frequency to be used in the distance measurement. Such an arrangement reduces system cost and complexity compared to a full duplex system. The simplex mode of operation is conceptually simpler, but requires tighter synchronization of events between the master and target unit(s), including the initiation of ranging signal sequences.

In this embodiment, the narrow bandwidth ranging signal multipath mitigation processor does not increase the ranging signal bandwidth. It uses different frequency components to advantageously allow the propagation of narrow bandwidth ranging signals. Further ranging signal processing may be performed in the frequency domain by utilizing super-resolution spectral estimation algorithms (MUSIC, rootMUSIC, ESPRIT) and/or statistical algorithms such as RELAX or assembling the synthetic ranging signal with a relatively large bandwidth. , further processing can be performed in the time domain by applying further processing to this signal. The different frequency components of the narrow-band ranging signal may be pseudorandomly selected, and may also be contiguous or spaced in frequency, which may have uniform and/or non-uniform spacing in frequency. be able to.

Embodiments extend multipath mitigation techniques. The signal model for narrowband ranging is complex exponential (as introduced elsewhere in this document), and the frequency of that complex exponential is directly proportional to the delay defined by the range plus the like term. , whose like delay is defined by the time delay associated with multipath. The model is independent of the actual implementation of the signal structure, eg, frequency stepping, linear frequency modulation, etc.

The frequency separation between the direct path and multipath is nominally extremely small and standard frequency domain processing is not sufficient to estimate the direct path range. For example, a stepped frequency ranging signal at a stepped rate of 100 KHz over 5 MHz over a range of 30 meters (100.07 ns delay) results in a frequency of 0.062875 rad/s. A multipath reflection with a path length of 35 meters results in a frequency of 0.073355. The separation is 0.0104792. The frequency resolution of the 50 sample observable has a unique frequency resolution of 0.12566 Hz. As a result, the direct path range cannot be accurately estimated using conventional frequency estimation techniques due to the separation of the direct path from the reflected path.

To overcome this limitation, embodiments use a unique combination of subspace-resolved high-resolution spectral estimation methodologies and implementations of multimodal cluster analysis. Subspace decomposition techniques rely on separating the estimated covariance matrix of the observed data into two orthogonal subspaces, the noise subspace and the signal subspace. The theory behind the subspace decomposition methodology is that the projection of observables onto the noise subspace consists only of noise, and the projection of observables onto the signal subspace consists of only signal.

Super-resolution spectrum estimation and RELAX algorithms are able to distinguish between closely located frequencies (sine waves) in the spectrum in the presence of noise. The frequencies do not have to be harmonically related, and unlike the Digital Fourier Transform (DFT), the signal model does not introduce any artificial periodicity. For a given bandwidth, these algorithms offer significantly higher resolution than the Fourier transform. Therefore, direct line of sight (DLOS) can be reliably distinguished from other multipaths (MP) with high accuracy. Similarly, applying the threshold method described later to an artificially produced synthetic wide-bandwidth ranging signal makes it possible to reliably distinguish DLOS from other paths with high accuracy.

According to an embodiment, digital signal processing (DSP) may be utilized by the multipath mitigation processor to reliably distinguish DLOS from other MP paths. Various super-resolution algorithms/techniques exist in spectral analysis (spectral estimation) techniques. Examples include subspace-based methods, namely Multiple Signal Characterization (MUSIC) or Root-MUSIC algorithms, Estimation of Signal Parameters by Rotation Invariant Techniques Algorithm (ESPRIT), Pisarenko Harmonic Decomposition ( PHD) algorithm, RELAX algorithm, etc.

The above super-resolution algorithms work on the assumption that the signals impinging on the antenna are not well correlated. Therefore, performance degrades severely in highly correlated signal environments such as may be encountered in multipath propagation. Multipath mitigation techniques may include a preprocessing scheme called spatial smoothing. As a result, the multipath mitigation process can be computationally intensive and complex, ie increasing the complexity of the system implementation. Multipath mitigation with low system computational cost and implementation complexity can be achieved by using a super-resolution matrix bundle (MP) algorithm. MP algorithms are classified as non-searching procedures. Therefore, it is computationally less complex and overcomes problems encountered in search procedures used in other super-resolution algorithms. Moreover, the MP algorithm is insensitive to correlated signals, requires only single channel estimation, and can also estimate delays associated with coherent multipath components.

In all of the super-resolution algorithms described above, the input (ie received) signal is modeled as a linear combination of complex exponential frequencies and their complex amplitudes. In the multipath case, the received signal is:

（１）

(1)

は、伝送される信号であり，ｆは、動作周波数であり、Ｌは、マルチパス成分の数であり、

及びτ_Ｋは、それぞれ、Ｋ番目のパスの複素減衰及び伝搬遅延である。マルチパス成分は、伝搬遅延が昇順に考慮されるように添え字を付される。結果として、このモデルでは、τ_０が、ＤＬＯＳパスの伝搬遅延を示す。明らかに、τ_０値は、全てのτ_Ｋのうちの最小値であるので、最も興味のあるものである。位相θ_Ｋは、通常、均一確率密度関数Ｕ（０，２π）を用いて１つの測定サイクルから別のサイクルまで無作為と仮定される。それゆえ、我々は、α_Ｋ＝一定（すなわち、一定値）であることを仮定する。 here,

is the signal to be transmitted, f is the operating frequency, L is the number of multipath components,

and τ _K are the complex attenuation and propagation delay of the Kth path, respectively. Multipath components are indexed such that propagation delays are considered in ascending order. As a result, in this model, τ ₀ denotes the propagation delay of the DLOS path. Clearly, the τ ₀ value is of most interest, as it is the smallest of all τ _K. The phase θ _K is normally assumed random from one measurement cycle to another with a uniform probability density function U(0,2π). Therefore, we assume that α _K =constant (ie a constant value).

The parameters α _K and τ _K are random, time-varying functions that reflect human and equipment movement in and around the building. However, since their rate of change is very slow compared to the measurement time interval, these parameters can be treated as time-varying random variables within a given measurement cycle.

All of these parameters are frequency dependent. because they relate to radio signal properties such as transmission and reflection coefficients. However, in embodiments, the operating frequency varies only slightly. Therefore, the parameters mentioned above can be assumed to be frequency independent.

（２）
として周波数領域において表わされ得、ここで、Ａ（ｆ）は、受信信号の複素振幅であり、（２π×τ_Ｋ）は、超分解能アルゴリズムによって推定される人工的な「周波数」であり、動作周波数ｆは、独立変数であり、α_Ｋは、Ｋ番目のパス振幅である。 Formula (1) is

(2)
where A(f) is the complex amplitude of the received signal, (2π×τ _K ) is the artificial “frequency” estimated by the super-resolution algorithm, The operating frequency f is the independent variable and α _K is the Kth pass amplitude.

In equation (2), the (2π×τ _K ) super-resolution estimate and subsequently the τ _K value are based on continuous frequencies. In practice, there are a finite number of measurements. Therefore, the variable f is discontinuous rather than continuous. Therefore, the complex amplitude A(f) can be calculated as follows.

（３）

(3)

は、不連続周波数ｆ_ｎにおける不連続複素振幅推定（すなわち、測定値）である。 here,

is the discontinuous complex amplitude estimate (ie, the measurement) at the discontinuous frequency _fn .

は、周波数ｆ_ｎの正弦波信号の振幅及び位相として、それがマルチパスチャネルを通って伝搬した後に、解釈され得る。全てのスペクトル推定ベースの超分解能アルゴリズムは、複素入力データ（すなわち、複素振幅）を要求することに留意する。 In formula (3),

can be interpreted as the amplitude and phase of a sinusoidal signal of frequency _fn after it propagates through a multipath channel. Note that all spectral estimation-based super-resolution algorithms require complex input data (ie complex amplitudes).

を複素信号（例えば、分析信号）に変換することができる。例えば、かかる変換は、ヒルベルト変換または他の方法を使用することによって達成され得る。しかしながら、短距離の場合では、値τ_０は非常に小さく、それは、非常に低い（２π×τ_Ｋ）「周波数」を結果としてもたらす。 In some cases, real signal data, e.g.

can be converted to a complex signal (eg, an analytic signal). For example, such transformations can be accomplished by using the Hilbert transform or other methods. However, in the short-range case, the value τ ₀ is very small, which results in a very low (2π×τ _K ) 'frequency'.

）のみが使用される場合には、推定される周波数の数が、（２π×τ_Ｋ）「周波数」のみではなくて、それらの組み合わせもまた含む。概して、未知の周波数の数の増大は、超分解能アルゴリズムの正確性に影響を及ぼす。それゆえ、他のマルチパス（ＭＰ）のパスからのＤＬＯＳパスの信頼できる及び正確な分離は、複素振幅推定を要求する。 These low "frequencies" pose problems for Hilbert transform (or other method) implementations. In addition to that, amplitude values (e.g.

) is used, the estimated number of frequencies includes not only (2π×τ _K ) “frequencies” but also combinations thereof. In general, increasing the number of unknown frequencies affects the accuracy of super-resolution algorithms. Therefore, reliable and accurate separation of DLOS paths from other multipath (MP) paths requires complex amplitude estimation.

を取得するタスクの間の方法及びマルチパス軽減プロセッサ動作の記載である。記載は、半二重動作モードに焦点を合わされるが、それは、全二重モードに容易に拡張され得ることに留意する。単信動作モードは、半二重モードのサブセットであるが、追加的な事象同期を要求する。 Below is the complex amplitude in the presence of multipath

is a description of the method and multipath mitigation processor operation during the task of obtaining . Note that the description focuses on half-duplex mode of operation, but it can be easily extended to full-duplex mode. Simplex mode of operation is a subset of half-duplex mode, but requires additional event synchronization.

In a half-duplex mode of operation, a reader (often referred to as a "master") and a tag (also referred to as a "slave" or "target") are controlled by a protocol that allows transmission only to In this mode of operation, the tag (target device) acts as a transponder. The tag receives the ranging signal from the reader (master device), stores it in memory, and then retransmits the signal back to the master after a certain time (delay).

Examples of ranging signals are shown in FIGS. 1 and 1A. An exemplary ranging signal utilizes different frequency components that are continuous. Other waveforms, including pseudo-random, spaced in frequency and/or time, or orthogonal, etc., may also be used as long as the ranging signal bandwidth remains narrow. In FIG. 1, the period T _f for all frequency components is long enough to obtain the ranging signal narrow bandwidth characteristic.

Another variant of a ranging signal with different frequency components is shown in FIG. It contains multiple frequencies (f ₁ , f ₂ , f ₃ , f ₄ , f _n ) that are transmitted over a long period of time to make the individual frequencies narrowband. Such a signal is more efficient, but it occupies a wide bandwidth and a wide bandwidth ranging signal affects the SNR, which in turn reduces the operating range. Also, such wide bandwidth ranging signals violate FCC requirements for the VHF band/or lower frequency bands. However, for certain applications, this wide bandwidth ranging signal allows easier integration into existing signaling and transmission protocols. Such signals also reduce track-to-locate time.

These multiple frequency (f ₁ , f ₂ , f ₃ , f ₄ , f _n ) bursts may also be continuous and/or pseudo-random, spaced apart in frequency and/or time. or orthogonal or the like.

Narrowband ranging mode provides accuracy in the form of instantaneous wideband ranging, as compared to broadband ranging, while increasing the range over which this accuracy can be achieved. This performance is achieved because, at a fixed transmit power, the SNR at the receiver of the narrowband ranging signal (within the appropriate signal bandwidth) is greater than the SNR at the receiver of the wideband ranging signal. The SNR gain is comparable to the ratio of the total bandwidth of the wideband ranging signal and the bandwidth of each channel of the narrowband ranging signal. This offers a good trade-off when very rapid ranging is not required, e.g. for stationary and slow moving objects, e.g. walking or running humans.

The master and tag devices are identical and can operate in either master or responder mode. All devices include a data/remote control communication channel. The devices can exchange information and the master device(s) can remotely control the tag device. In this example depicted in FIG. 1, during operation of the master (i.e., reader), the multipath mitigation processor generates ranging signals to the tag(s) so that after a fixed delay, the master/reader receives repeated ranging signals from the tag(s).

推定値を決定する。式（３）において、

が、一方向レンジング信号トリップについて定義されることに留意する。実施形態では、レンジング信号が、ラウンドトリップを行う。換言すれば、それは、マスタ／読み取り機から対象／スレーブへの及び対象／スレーブからマスタ／読み取り機に戻る両方向に移動する。それゆえ、マスタに戻って受信される、このラウンドトリップ信号複素振幅は、以下のように計算され得る。 The master's multipath mitigation processor then compares the received ranging signal with that originally transmitted from the master, in the form of amplitude and phase for all frequency components _fn .

Determine an estimate. In formula (3),

is defined for a one-way ranging signal trip. In an embodiment, the ranging signal makes round trips. In other words, it moves in both directions, from the master/reader to the target/slave and from the target/slave back to the master/reader. Therefore, this round-trip signal complex amplitude, received back at the master, can be calculated as follows.

（４）

(4)

及び

を含む、複素振幅ならびに位相値を推定するために利用可能な多くの技法が存在する。実施形態によれば、複素振幅決定は、マスタ及び／またはタグ受信機ＲＳＳＩ（受信信号強度インジケータ）値から導出される

値に基づく。位相値

は、読み取り機／マスタによって受信されて戻されたベースバンドレンジング信号位相と、元の（すなわち、読み取り機／マスタによって送信された）ベースバンドレンジング信号位相を比較することによって取得される。それに加えて、マスタ及びタグデバイスは、独立したクロックシステムを有するので、デバイス動作の詳細な説明は、位相推定誤差へのクロック正確性の影響の分析によって補われる。上記が示すように、一方向振幅

値は、対象／スレーブデバイスから直接取得可能である。しかしながら、一方向位相

値は、直接測定されることができない。 For example, adaptive filtering

as well as

There are many techniques available for estimating complex amplitude as well as phase values, including . According to embodiments, the complex amplitude determination is derived from master and/or tag receiver RSSI (Received Signal Strength Indicator) values

Based on value. phase value

is obtained by comparing the baseband ranging signal phase received back by the reader/master and the original (ie, transmitted by the reader/master) baseband ranging signal phase. In addition, since the master and tag devices have independent clock systems, a detailed description of device operation is supplemented by an analysis of the impact of clock accuracy on phase estimation error. As the above shows, the unidirectional amplitude

Values can be obtained directly from the target/slave device. However, the one-way phase

Values cannot be measured directly.

In an embodiment, the ranging baseband signal is the same as depicted in FIG. However, for the sake of brevity, it is herein assumed that the ranging baseband signal consists only of two frequency components, each containing multiple periods of cosine or sine waves of different frequencies _F1 and _F2 . assumed. Note that F ₁ =f ₁ and F ₂ =f ₂ . The number of cycles is L in the first frequency component and the number of cycles is P in the second frequency component. Note that L may or may not equal P. This is because if Tf = constant, each frequency component can have a different number of cycles. Also, there is no time separation between each frequency component, and both F ₁ and F ₂ start with an initial phase equal to zero.

3A, 3B and 3C depict block diagrams of master or slave units (tags) of the RF mobile tracking and location system. _FOSC refers to the frequency of the device system clock (crystal oscillator 20 in FIG. 3A). All frequencies generated within the device are generated from this system clock crystal oscillator. The following definitions are used. That is, M is the master device (unit) and AM is the tag (target) device (unit). A tag device is operating in answerer mode and is referred to as an answerer (AM) unit.

であるからである。 In a preferred embodiment, the device consists of RF front-end and RF back-end baseband and multipath mitigation processors. The RF backend, baseband and multipath mitigation processors are implemented in FPGA 150 (see FIGS. 3B and 3C). The system clock generator 20 (see FIG. 3A) operates at F _OSC =20 MHz
Or oscillate at ω _OSC =2π×20×10 ⁶ . This is the ideal frequency. Because in real devices the system clock frequency is not necessarily equal to 20 MHz, i.e.

Because it is.

及び

に留意する。

as well as

Note

Note that F _OSC frequencies other than 20 MHz can be used without any impact on system performance.

The electronic configuration of both units (master and tag) is identical and the different operating modes are software programmable. The baseband ranging signals are generated in digital form by the master FPGA 150, blocks 155-180 (see FIG. 2B). It consists of two frequency components each containing multiple cycles of cosine or sine waves of different frequencies. At the beginning, t=0, FPGA 150 (FIG. 3B) in the master device outputs digital baseband ranging signals to its upconverter 50 via I/Q DACs 120 and 125 . FPGA 150 starts at frequency F ₁ and after time T ₁ begins generating frequency F ₂ for time period T ₂ .

Since the crystal oscillator frequency can differ from 20 MHz, the actual frequencies generated by the FPGA will be F ₁ ^γM and F ₂ ^γM . Also, time T ₁ becomes T ₁ ^βM and T ₂ becomes T ₂ ^βM . Also, T ₁ , T ₂ , F ₁ , F ₂ are such that F ₁ γ ^M * T ₁ β ^M = F ₁ T ₁ and F ₂ γ ^M * T ₂ β ^M = F ₂ T ₂ , where both F ₁ T ₁ and F ₂ T ₂ are assumed to be integers. That means that the initial phases of _F1 and _F2 are equal to zero.

及び

ここで、

及び

は一定の係数である。同様に、周波数合成器２５からの出力周波数ＴＸ＿ＬＯ及びＲＸ＿ＬＯ（ミキサ５０及び８５のためのＬＯ信号）は、一定の係数によって表現され得る。これらの一定の係数は、マスタ（Ｍ）及び応答機（ＡＭ）についても同じであり、違いは、各デバイスのシステム水晶発振器２０のクロック周波数にある。 Since all frequencies are generated from the system crystal oscillator 20 clock, the outputs of the master baseband I/Q DAC(s) 120 and 125 are:

as well as

here,

as well as

is a constant coefficient. Similarly, the output frequencies TX_LO and RX_LO from frequency synthesizer 25 (the LO signals for mixers 50 and 85) can be expressed by constant coefficients. These constant coefficients are the same for the master (M) and transponder (AM), the difference being the clock frequency of the system crystal oscillator 20 of each device.

The master (M) and answerer (AM) operate in half-duplex mode. The master RF front end upconverts the baseband ranging signal generated by the multipath mitigation processor using a quadrature upconverter (ie, mixer) 50 and transmits the upconverted signal. After the baseband signal is transmitted, the master switches from TX to RX mode using the TX/RX switch 15 in the RF front end. The transponder receives the signal and downconverts it back using the mixer 85 (producing the first IF) and the ADC 140 (producing the second IF) in its RF front end.

This second IF signal is then digitally filtered in the processor of the transponder RF backend using digital filter 190 to provide RF backend quadrature mixer 200, digital I/Q filters 210 and 230, It is further downconverted to a baseband ranging signal using digital quadrature oscillator 220 as well as adder 270 . This baseband ranging signal is stored in the transponder's memory 170 using the RAM data bus controller 195 and control logic 180 .

である。マスタは、応答機の伝送を受信して、そのＲＦバックエンドの直交ミキサ２００、デジタルＩ及びＱフィルタ２１０ならびに２３０、デジタル直交発振器２２０（図３Ｃを参照）を使用して、受信信号をベースバンド信号にダウンコンバートし戻す。 The responder then switches from RX to TX mode using switch 15 in the RF front end and begins retransmitting the stored baseband signal after a fixed delay t _RTX . Note that the delay is measured at the AM (Answer Machine) system clock. therefore,

is. The master receives the transponder's transmission and uses its RF backend's quadrature mixer 200, digital I and Q filters 210 and 230, and digital quadrature oscillator 220 (see FIG. 3C) to convert the received signal to baseband. Downconvert back to the signal.

The master then uses multipath mitigation processor arctangent block 250 and phase comparison block 255 to calculate the phase difference between F ₁ and F ₂ in the received (ie, recovered) baseband signal. Amplitude values are derived from RSSI block 240 in the RF backend.

To improve estimation accuracy, it is always desirable to improve the SNR of the amplitude estimate from block 240 and the phase difference estimate from block 255 . In a preferred embodiment, a multipath mitigation processor computes amplitude and phase difference estimates for many time instances over the ranging signal frequency component period (T _f ). These values improve the SNR when averaged. SNR improvement may be a goal proportional to √N, where N is some instance when the amplitude and phase difference values are taken (ie, determined).

及び

形式に変換され得る。 Another approach to SNR improvement is to determine amplitude and phase difference values by applying adaptive filtering techniques over time. Yet another approach is to measure the phase and amplitude of the received (i.e. repeated) baseband ranging signal frequency component by sampling it and converting it to the original (i.e. by the master/reader) in I/Q form. (transmitted) baseband ranging signal frequency components by integrating over period _T≤Tf . Integration has the effect of averaging multiple instances of amplitude and phase in I/Q format. The phase and amplitude values are then obtained from the I/Q format as

as well as

can be converted into the form

Assume that at t=0, the master baseband processors (both in FPGA 150) initiate a baseband ranging sequence under the master's multipath processor control.

where T _f ≧T ₁ ^βM .

The phases at the master DAC(s) 120 and 125 outputs are:

を有することに留意する。 DACs 120 and 125 have internal propagation delays independent of the system clock.

Note that we have

をもたらす。 Similarly, transmitter circuitry 15, 30, 40, and 50 provide additional delay independent of the system clock.

bring.

As a result, the phase of the RF signal transmitted by the master is calculated as follows.

The RF signal from the master (M) experiences a phase shift φ ^MULT that correlates with multipath phenomena between the master and tags.

The φ ^MULT value depends on the transmitted frequencies, eg F ₁ and F ₂ . The responder (AM) receiver cannot resolve each path due to the limited (ie, narrow) bandwidth of the RF portion of the receiver. Therefore, after a certain time, say 1 microsecond (corresponding to a flight of about 300 meters), when all reflected signals have arrived at the receiver antenna, the following formula applies.

At the first downconverter, AM (responder) receiver in element 85, the output, eg, first IF, signal phase is:

は、システムクロックに依存しないことに留意する。ＲＦフロントエンドのフィルタ及び増幅器（要素９５～１１０及び１２５）を通過した後、第１のＩＦ信号は、ＲＦバックエンドのＡＤＣ１４０によってサンプリングされる。ＡＤＣ１４０は、入力信号（例えば、第１のＩＦ）をアンダーサンプリングしていることが仮定される。それゆえ、ＡＤＣはまた、第２のＩＦを作り出すダウンコンバータのように作動する。第１のＩＦフィルタ、増幅器、及びＡＤＣは、伝搬遅延時間を追加する。ＡＤＣ出力（第２のＩＦ）において、

である。 Propagation delay in the receiver RF section (elements 15 and 60-85)

Note that is independent of the system clock. After passing through the RF front end filters and amplifiers (elements 95-110 and 125), the first IF signal is sampled by the RF back end ADC 140 . ADC 140 is assumed to be under-sampling the input signal (eg, first IF). Therefore, the ADC also acts like a downconverter creating a second IF. The first IF filter, amplifier and ADC add propagation delay time. At the ADC output (second IF),

is.

である。 In FPGA 150, the second IF signal (from the ADC output) is filtered by digital filter 190 in the RF backend, and passed through a third downconverter (i.e., quadrature mixer 200, digital filters 230 and 210, and digital quadrature oscillator 220). ) back to the baseband ranging signal, summed in adder 270 and stored in memory 170 . At the third downconverter output (i.e. quadrature mixer):

is.

は、システムクロックに依存しないことに留意する。 Propagation delay in FIR section 190

Note that is independent of the system clock.

に留意する。 After the RX to TX delay, the stored (in memory 170) baseband ranging signal from the master (M) is retransmitted. TX delay from RX

Note

By the time the signal from the responder arrives at the receiver antenna of the master (M), the RF signal from the responder (AM) experiences another phase shift φ ^MULT that correlates with multipath. As noted above, this phase shift occurs after a period of time when all reflected signals arrive at the master's receiver antenna.

At the master receiver, the signal from the responder undergoes the same down-conversion process as at the responder's receiver. The result is the recovered baseband ranging signal originally transmitted by the master.

である。 For the first frequency component _F1 ,

is.

である。 For the second frequency component F2,

is.

を行い、ここで、Ｔ_{Ｄ＿Ｍ－ＡＭ}は、マスタ（Ｍ）及び応答機（ＡＭ）回路を通る伝搬遅延である。 permutation,

where _{TD_M-AM} is the propagation delay through the master (M) and transponder (AM) circuits.

である。 where φ _{BB_M−AM} (0) is the LO phase shift at time t=0 from the master (M) and transponder (AM) frequency mixers, including the ADC(s).
again,

is.

である。 For the first frequency component F1,

is.

である。 Subsequently, for the first frequency component F1,

is.

である。 For the second frequency component F2,

is.

である。 Subsequently, for the second frequency component F2,

is.

を行い、ここで、αは一定である。 Furthermore, permutation,

, where α is constant.

（５）
である。 The final phase equation is

(5)
is.

となり、ここで、ｉ＝２、３、４・・・・・・・・・・・・・・、

は、

に等しい。 From equation (5),

, where i=2, 3, 4,

teeth,

be equivalent to.

は、

となる。 For example, the difference in time instances t1 and t2

teeth,

becomes.

差を求めるために、我々は、Ｔ_{Ｄ＿Ｍ－ＡＭ}を知る必要がある。すなわち、

To find the difference, we need to know _{TD_M-AM} . i.e.

where T _{LB_M} and T _{LB_AM} are the propagation delays through the master (M) and responder (AM) TX and RX circuits measured by placing the device in loopback mode. Note that the master and responder devices can automatically measure T _{LB_M} and T _{LB_AM} and we also know the t _RTX value.

値が、以下のように求められ得る。 From the above equation and the t _RTX value, T _{D_M-AM} can be determined, so that for given t ₁ and t ₂

The value can be determined as follows.

（６）

(6)

（６Ａ）
となる。 Or, assuming β ^M =β ^AM =1,

(6A)
becomes.

From equation (6) it can be concluded that at the operating frequency(s) ranging signal(s), complex amplitude values can be obtained from processing the returned baseband ranging signal.

はゼロに等しいことが仮定され得る。必要に応じて、

値（位相初期値）は、特許文献１に記載されるような狭帯域幅レンジング信号方法を使用して、ＴＯＡ（到着時間）を決定することによって求められ得、その特許文献１は、その全体が参照によって本明細書に組み込まれる。この方法は、レンジング信号のラウンドトリップ遅延を推定し、それは、

に等しく、

値が、以下の式から求められ得る。 The subspace algorithm is insensitive to constant phase offsets, so the initial phase value

can be assumed to be equal to zero. as needed,

The value (phase initial value) can be determined by determining the TOA (time of arrival) using the narrow bandwidth ranging signal method as described in US Pat. is incorporated herein by reference. This method estimates the round-trip delay of the ranging signal, which is

equal to

The value can be determined from the following formula.

または、

or,

が、マルチパスプロセッサの逆正接ブロック２５０によって計算される。ＳＮＲを改良するために、マルチパス軽減プロセッサの位相比較ブロック２５５が、式（６Ａ）を使用して多くの実例ｎ（ｎ＝２、３、４・・・・・・・・・・・・・・・）について、

を計算し、次いで、それらを平均して、ＳＮＲを改良する。

に留意する。 In the preferred embodiment, the returned baseband ranging signal phase value

is computed by the arctangent block 250 of the multi-pass processor. To improve the SNR, the phase comparison block 255 of the multipath mitigation processor uses equation (6A) to calculate a number of instances n (n=2, 3, 4, . . . ). ···)about,

and then average them to improve the SNR.

Note

From equations 5 and 6 it becomes clear that the recovered (ie received) baseband ranging signal has the same frequency as the original baseband signal transmitted by the master. Therefore, there is no frequency translation, despite the fact that the master (M) and transponder (AM) system clocks may be different. Since the baseband signal consists of several frequency components, each component consists of multiple periods of a sine wave. Also, by sampling the individual frequency components of the received baseband signal together with the corresponding individual frequency components of the original (i.e., transmitted by the master) baseband signal, and over a period _T≤Tf , the resulting It is also possible to estimate the phase and amplitude of the received ranging signal by integrating the resulting signal as .

を生成する。マスタによって送信された各ベースバンド信号の個々の周波数成分は、Ｔ_{Ｄ＿Ｍ－ＡＭ}の時間だけシフトされる必要があることに留意する。統合動作は、（例えば、ＳＮＲを増大させる）振幅及び位相の複数の実例を平均するという効果をもたらす。位相及び振幅値は、Ｉ／Ｑ形式から

及び

形式に変換され得ることに留意する。 This operation is the complex amplitude value of the received ranging signal in I/Q format.

to generate Note that the individual frequency components of each baseband signal transmitted by the master must be shifted by a time of _{TD_M-AM} . The integration operation has the effect of averaging multiple instances of amplitude and phase (which increases SNR, for example). Phase and amplitude values are obtained from the I/Q format

as well as

Note that it can be converted to the format

及び

形式への変換の本方法は、図３Ｃにおける位相比較ブロック２５５において実現され得る。それゆえ、ブロック２５５の設計及び実現形態に応じて、式（５）に基づく好ましい実施形態の方法か、またはこの欄に記載される代替の方法のいずれかが、使用され得る。 Sampling, integration over periods of _T≤Tf , and thereafter, from the I/Q format

as well as

This method of conversion to format may be implemented in phase comparison block 255 in FIG. 3C. Therefore, depending on the design and implementation of block 255, either the preferred embodiment method based on equation (5) or the alternative methods described in this section may be used.

Although the ranging signal bandwidth is narrow, the frequency difference f _n −f ₁ may be relatively large, eg, on the order of several megahertz. As a result, the receiver bandwidth must be kept wide enough to pass all of the f ₁ :f _n ranging signal frequency components. The wide bandwidth of this receiver affects the SNR. by a digital narrowband filter in which the received ranging signal baseband frequency components are adjusted for each individual frequency component of the received baseband ranging signal to reduce the receiver effective bandwidth and improve SNR; It can be filtered by the RF backend processor in FPGA 150 . However, this large number of digital filters (the number of filters equals the number of individual frequency components, n) puts an additional burden on FPGA resources, increasing its cost, size, and power consumption.

In the preferred embodiment only two narrow bandwidth digital filters are used. That is, one filter can always be adjusted for frequency component f ₁ and the other filter for all other frequency components, ie f ₂ : f _n . Multiple instances of ranging signals are sent by the master. Each example consists of only two frequencies _f1 : _f2 ; _f1 : _f3 ...; _f1 : _fi ;...; _f1 : _fn . A similar approach is also possible.

Note also that it is perfectly possible to keep the baseband ranging signal components to only two (or one) generating the rest of the frequency components by adjusting the frequency synthesizer, e.g. changing K _SYN . I want you to Preferably, the LO signals for the upconverter and downconverter mixers are generated using direct digital synthesis (DDS) techniques. For high VHF band frequencies, this may result in an undesirable burden on the transceiver/FPGA hardware. However, for lower frequencies this may be a useful approach. Analog frequency synthesizers can also be used, but may take more time to stabilize after the frequency is changed. Also, in the case of analog synthesizers, two measurements at the same frequency need to be made to eliminate possible phase offsets after changing the frequency of the analog synthesizer.

が計算されるとき、Ｔ_{ＬＢ＿ＡＭ}及びｔ_ＲＴＸの両方が、マスタ（Ｍ）クロックにおいて測定（計数）される。これは、誤差

（７）
をもたらす。 The actual _{TD_M-AM} used in the above equation is measured at both the master (M) and responder (AM) system clocks, e.g., T _{LB_AM} and t _RTX are counted at the responder (AM) clock. , _{TLB_M} are counted in the master (M) clock. however,

When is calculated, both _{T_LB_AM} and _{t_RTX} are measured (counted) at the master (M) clock. This is the error

(7)
bring.

Phase estimation error (7) affects accuracy. Therefore, it is necessary to minimize this error. The contribution from time t _RTX is removed if β ^M =β ^AM , in other words if all master(s) and responder (tag) system clocks are synchronized.

In preferred embodiments, the master and transponder units (devices) can synchronize clocks with any of the devices. For example, a master device can act as a reference. Clock synchronization is achieved by using a remote control communication channel to adjust the frequency of temperature compensated crystal oscillator TCXO 20 under FPGA 150 control. The frequency difference is measured at the output of the adder 270 of the master device while the selected transponder device is transmitting the carrier signal.

The master then sends a command to the transponder to increase/decrease the TCXO frequency. This procedure may be repeated several times to achieve better accuracy by minimizing the frequency at the adder 270 output. Note that in the ideal case the frequency at the adder 270 output should equal zero. An alternative method is to measure the frequency difference and correct the estimated phase without adjusting the TCXO frequency of the transponder.

Although β ^M −β ^AM can be significantly reduced, phase estimation error exists when β ^M ≠1. In this case, the margin of error depends on the long-term stability of the reference device (usually the master (M)) clock generator. Additionally, the process of clock synchronization, especially with multiple units in the field, can take a significant amount of time. During the synchronization process, the track-and-locate system becomes partially or completely inoperable, which adversely affects system readiness and performance. In this case, the method described above, which does not require a TCXO frequency adjustment of the transponder, is preferred.

Commercially available (off-the-shelf) TCXO components have a high degree of accuracy and stability. Specifically, TCXO components for GPS commercial applications are highly accurate. With these devices, the impact of phase error on localization accuracy can be less than 1 meter without the need for frequent clock synchronization.

を取得した後、更なる処理（すなわち、超分解能アルゴリズムの実行）が、ソフトウェアベースの構成要素において実現され、それは、マルチパス軽減プロセッサの一部分である。このソフトウェア構成要素は、ＦＰＧＡ１５０（図示しない）に埋め込まれるマスタ（読み取り機）ホストコンピュータＣＰＵ及び／またはマイクロプロセッサにおいて実現され得る。好ましい実施形態では、マルチパス軽減アルゴリズム（複数可）ソフトウェア構成要素が、マスタホストコンピュータＣＰＵによって実行される。 A narrow bandwidth ranging signal multipath mitigation processor calculates the returned narrow bandwidth ranging signal complex amplitude

After obtaining , further processing (ie, running a super-resolution algorithm) is implemented in a software-based component, which is part of the multipath mitigation processor. This software component may be implemented in a master (reader) host computer CPU and/or microprocessor embedded in FPGA 150 (not shown). In the preferred embodiment, the multipath mitigation algorithm(s) software component is executed by the master host computer CPU.

The super-resolution algorithm(s) produce an estimate of the (2π×τ _K ) “frequency”, eg, the τ _K value. In the final step, the multipath mitigation processor selects τ (ie, the DLOS delay time) with the smallest value.

In certain cases where the ranging signal narrow bandwidth requirements are relaxed to some extent, the DLOS path can be separated from the MP path by utilizing a continuous (in time) chirp. In the preferred embodiment, this continuous chirp is linear frequency modulation (LFM). However, other chirp waveforms may also be used.

ラジアンのチャープレートを与える。複数のチャープが、伝送されて、受信し戻される。チャープ信号は、デジタル式に発生され、各チャープは、同じ位相で開始されることに留意する。 Assume that a chirp with a bandwidth of B and a period of T is transmitted under multipath mitigation processor control. it is every second

Gives the char rate in radians. Multiple chirps are transmitted and received back. Note that the chirp signal is digitally generated and each chirp starts at the same phase.

In the multipass processor each received single chirp is position adjusted so that the returned chirp is from the middle of the region of interest.

であり、ここで、ω_０は、０＜ｔ＜Ｔの場合の初期周波数である。
単一遅延ラウンドトリップτ、例えば、マルチパスがない場合、戻された信号（ｃｉｒｐ）は、ｓ（ｔ－τ）である。 The chirp wave form is

where ω ₀ is the initial frequency for 0<t<T.
For a single delay round trip τ, eg, no multipath, the returned signal (cirp) is s(t−τ).

（８）
であり、
ここで、ｅｘｐ（－ｉｗ_０τ_ｋ）は振幅であり、２βτは周波数であり、０≦ｔ≦Ｔである。最後の項は位相であり、それは無視してよいことに留意する。 The multipath mitigation processor then “deramps” s(t−τ) by performing complex conjugate mixing with the originally transmitted chirp. The resulting signal is a complex sine wave

(8)
and
where exp(-iw ₀ τ _k ) is the amplitude, 2βτ is the frequency, and 0≦t≦T. Note that the last term is the phase, which can be ignored.

（９）
から成り、ここで、Ｌは、ＤＬＯＳパスを含む、レンジング信号パスの数であり、０≦ｔ≦Ｔである。 In the multipath case, the deramped composite signal consists of multiple complex sinusoids

(9)
where L is the number of ranging signal paths, including DLOS paths, and 0≤t≤T.

（１０）
ここで、Ｎは、チャープの数であり、

ρ＝Ｔ＋ｔ_ｄｅａｄ、ｔ_ｄｅａｄは、２つの連続的なチャープ間の不動作時間帯であり、２βτ_ｋは、人工的な遅延「周波数」である。再び、最も興味のあるものは最低「周波数」であり、それは、ＤＬＯＳパス遅延に対応する。 Multiple chirps are transmitted and processed. Each chirp is individually handled/processed as described above. The multipath mitigation processor then assembles the individual chirp results,

(10)
where N is the number of chirps,

ρ=T+t _dead , where t _dead is the dead time period between two consecutive chirps and 2βτ _k is the artificial delay “frequency”. Again, of most interest is the lowest "frequency", which corresponds to the DLOS path delay.

は、時間、すなわち、

における複素正弦波の合計のＮ個のサンプルとして考えられ得る。それゆえ、サンプルの数は、複数のＮ、例えば、αＮ；α＝１，２，…であり得る。 In formula (10),

is the time, i.e.

can be thought of as the N samples of the sum of the complex sinusoids at . Therefore, the number of samples can be multiple N, eg, αN; α=1, 2, .

From equation (10), the multipath mitigation processor produces αN complex amplitude samples in the time domain that are used in further processing (ie, running the super-resolution algorithm). This further processing is implemented in a software component, which is part of the multipath mitigation processor. This software component may be executed by a master (reader) host computer CPU and/or by a microprocessor embedded within FPGA 150 (not shown), or both. In the preferred embodiment, multipath mitigation algorithm(s) software is executed by the master host computer CPU.

The super-resolution algorithm(s) produces estimates of 2βτ _k 'frequencies', eg, τ _K values. In the final step, the multipath mitigation processor selects τ with the smallest value, the DLOS delay time.

A special processing method is described that can serve as an alternative to the super-resolution algorithm and is called the "threshold technique". In other words, it is used to enhance reliability and accuracy in distinguishing DLOS paths from other MP paths using artificially generated synthetic wide-bandwidth ranging signals.

（１１）
に変換され得る。ｓ（ｔ）は、周期１／Δｔで周期的であること、及び任意の整数ｋについて、ｓ（ｋ／Δｔ）＝２Ｎ＋１であり、それは信号のピーク値であることが容易に実証される。ここで、図１及び図１Ａにおいて、ｎ＝Ｎである。 The frequency-domain baseband ranging signal shown in FIGS. 1 and 1A is the time-domain baseband signal s(t), i.e.

(11)
can be converted to It is easily demonstrated that s(t) is periodic with period 1/Δt, and that for any integer k, s(k/Δt)=2N+1, which is the peak value of the signal. Here, in FIGS. 1 and 1A, n=N.

FIG. 4 shows two periods of s(t) for N=11 and Δf=250 kHz. The signal appears as a series of pulses of height 2N+1=23 separated by 1/Δf=4 microseconds. Between pulses there is a sinusoidal waveform with variable amplitude and 2N zeros. The wide bandwidth of the signal can be attributed to the high pulse narrowness. It can also be seen that the bandwidth extends from zero frequency to NΔf=2.75 MHz.

The basic idea of the threshold method used in the preferred embodiment is to enhance the reliability and accuracy of artificially generated synthetic wide-bandwidth ranging in distinguishing DLOS paths from other MP paths. be. The threshold method detects when the start of the leading edge of the wideband pulse arrives at the receiver. Due to filtering in the transmitter and receiver, the leading edge does not rise instantly, but rises noiselessly with a smoothly increasing slope. The TOA of the leading edge is measured by detecting when the leading edge exceeds a predetermined threshold T.

A small threshold is desirable because it will be exceeded more quickly and the error delay τ between the true onset of the pulse and exceeding the threshold is small. Therefore, any pulse replication arriving due to multipath has no effect if the start of replication has a delay greater than τ. However, the presence of noise imposes a limit on how small the threshold T can be. One technique to reduce the delay τ is to use the derivative of the received pulse instead of the pulse itself, because the derivative rises faster. The second derivative has an even faster rise. Higher order derivatives can be used, but in practice they can raise the noise level to unacceptable values, so a thresholded second derivative is used.

The 2.75 MHz broadband signal depicted in FIG. 4 has a fairly wide bandwidth, which is not suitable for measuring range by the method described above. That method requires that the transmitted pulses each have a zero signal predecessor. However, the goal can be achieved by modifying the signal such that the sinusoidal waveform between pulses is essentially canceled. In the preferred embodiment, it is done by constructing a waveform that closely approximates the signal on selected intervals between high pulses, and then subtracting it from the original signal.

The technique can be illustrated in FIG. 1 by applying it to a signal. The two black dots shown on the waveform are the endpoints of interval I centered between the first two pulses. The left and right endpoints of interval I have been experimentally determined to give the best results and are respectively below.

（１２）

(12)

An attempt is made to generate a function g(t) that essentially cancels the signal s(t) over this interval, but does less harm outside the interval. Equation (11) shows that s(t) is a sine wave sinπ(2N+1)Δft modulated by 1/sinπΔft, so first, a function h(t) that is very close to 1/sinπΔft over interval I is found, then form g(t) as the product.

（１３）

(13)

h(t) is generated by summing:

（１４）

(14)

（１５）
であり、係数ａ_ｋは、区間Ｉ上で、最小二乗誤差を最小限にするように選択される。 here,

(15)
and the coefficients a _k are chosen to minimize the least squared error on interval I.

（１６）

(16)

The solution is easily obtained by taking the partial derivatives J with respect to a _k and setting them equal to zero. The result is a system of M+1 linear equations.

（１７）

(17)

（１８）
である。 It can be solved for a _k , where

(18)
is.

（１９） then

(19)

（２０） Using the definition of the function φ _k (t) given by (12),

(20)

（２１） g(t) is subtracted from s(t) to obtain the function r(t), which should essentially cancel s(t) over interval I. As shown in the appendix, a good choice for the upper bound M for summation in equation (20) is M=2N+1. Using this value and the results from the appendix,

(21)

here,
b ₀ =1-(1/2)a _2N+1
b _k =2−(1/2)a _2(N−k)+1 for k=1, 2, . . . , N b _k =−(1/2)a _2(k−N)−1 k=N+1 , N+2, . . . , 2N+1, c=-a ₀
(22)

From equation (17) it can be seen that a total of 2N+3 frequencies (including the zero frequency DC term) are required to obtain the desired signal r(t). FIG. 5 shows the resulting signal r(t) for the original signal s(t) shown in FIG. 1, where N=11. In this case, the construction of r(t) requires 25 carriers (including the DC term _b0 ).

The key features of r(t) as constructed above are:

1. The lowest frequency is zero Hz and the highest frequency is (2N+1)Δf [Hz] as can be seen from (14). Therefore, the total bandwidth is (2N+1)Δf [Hz].

2. All carriers are cosine functions (including DC) spaced apart by Δf except for one carrier, which is a sine function located at frequency (N+1/2)Δf.

3. The original signal s(t) has period 1/Δf, while r(t) has period 2/Δf. The first half of each period of r(t), which is the full period of s(t), contains the canceled portion of the signal, and the second half of the period of r(t) is the large oscillation portion. Therefore, the cancellation of the preceding wave only occurs in every other period of s(t).

This occurs because the canceling function g(t) actually strengthens s(t) in every other period. The reason is that g(t) reverses its polarity in all peaks of s(t), whereas s(t) does not. A method for including a portion where all periods of s(t) are canceled to increase the processing gain by 3 dB is described below.

4. The length of the canceled portion of s(t) is approximately 80-90% of 1/Δf. Therefore, Δf should be small enough to make this length long enough to remove any residual signal from the leading non-zero part of r(t) due to multipath. .

5. Immediately after each zero portion of r(t) is the first cycle of the oscillating portion. In a preferred embodiment, in the TOA measurement method as described above, the first half of this cycle is used to measure the TOA, specifically the beginning of its rise. Note that the peak value of this first half cycle (called the main peak) is somewhat larger than the corresponding peak in s(t) located at approximately the same time. The width of the first half cycle is roughly inversely proportional to NΔf.

6. A large amount of processing gain can be achieved by:

(a) Use a repetition of the signal r(t), since r(t) is periodic with period 2/Δf. An additional 3 dB of processing gain is also possible by methods described later.

(b) Narrow band filtering. Since each of the 2N+3 carriers is a narrowband signal, the occupied bandwidth of the signal is much smaller than that of a wideband signal spread over the entire allocated band of frequencies.

For the signal r(t) shown in FIG. 5, where N=11 and Δf=250 kHz, the length of the canceled portion of s(t) is approximately 3.7 microseconds or 1,110 meters. . This is more than enough to remove residual signal from the leading non-zero part of r(t) due to multipath. The main peak has a value of about 35 and the maximum magnitude in the precursor (ie, cancellation) region is about 0.02, which is 65 dB below the main peak. This is desirable for good performance using the TOA measurement threshold technique as described above.

The use of fewer carriers is depicted in FIG. 6, which illustrates a signal generated using Δf=850 kHz, N=3, and M=2N+1=7 for only 2N+3=9 carriers in all. . In this case the period of the signal is only 2/Δf≈2.35 microseconds compared to the signal in FIG. 5, which has a period of 8 microseconds. Since this embodiment has more cycles per unit time, it can be expected that more processing gain can be achieved.

However, since fewer carriers are used, the amplitude of the main peak is about ⅓ of its previous magnitude, which tends to eliminate the extra processing gain expected. Also, the length of the zero signal predecessor segment is shorter, about 0.8 microseconds or 240 meters. This should still be sufficient to remove residual signal from the leading non-zero part of r(t) due to multipath. Note that the total bandwidth of (2N+1)Δf=5.95 MHz is approximately the same as before, and that the half-cycle width of the main peak is also approximately the same. Since fewer carriers are used, there should be some extra processing gain when each carrier is narrowband filtered at the receiver. Moreover, the maximum magnitude in the precursor (ie, cancellation) region is now approximately 75 dB below the main peak, an improvement of 10 dB from the previous example.

Transmission at RF frequencies. Heretofore, r(t) is described as a baseband signal for the sake of simplicity. However, it can be converted up to RF, transmitted, received and then reconstructed as a baseband signal at the receiver. To illustrate, consider what happens to one of the frequency components ω _k in the baseband signal r(t) traveling through one of the multipath propagation paths with index j ( Frequency in radians/second is used for notational simplicity).

b _k cos ω _k t (at the baseband in the transmitter)
b _k cos(ω+ω _k )t (transformed by frequency ω up to RF)
a _j b _k cos[(ω+ω _k )(t−τ _j )+φ _j ] (at the receiver antenna)
a _j b _k cos [ω _k (t−τ _j )+φ _j +θ] (translated by frequency −ω to baseband)
(23)

Here it is assumed that the transmitter and receiver are frequency synchronized. The parameter b _k is the kth coefficient in equation (21) for r(t). The parameters τ _j and φ _j are the path delay and phase shift (due to the reflector dielectric properties) of the j th propagation path, respectively. The parameter θ is the phase shift that occurs during downconversion to baseband at the receiver. A similar sequence of functions can be expressed for the sine component of equation (21).

As long as the zero signal predecessor in r(t) has a length sufficiently greater than the maximum significant propagation delay, the final baseband signal in equation (20) will still have a zero signal predecessor. Important to note. Of course, when all frequency components (subscript k) on all paths (subscript j) are combined, the baseband signal at the receiver is a distorted form of r(t), including all phase shifts. become.

Continuous carrier transmission and signal reconstruction are illustrated in FIGS. 1 and 1A. It is assumed that the transmitter and receiver are time and frequency synchronized and that the 2N+3 transmitted carriers need not be transmitted simultaneously. As an example, consider the transmission of a signal whose baseband representation is that of FIGS. 1A and 6. FIG.

In FIG. 6, it is assumed that N=3 and that each of the 9 frequency components is transmitted continuously for 1 millisecond. The start and end times for each frequency transmission are known at the receiver, so it can continuously start and end its reception of each frequency component at their respective times. Since the signal propagation time is very short compared to 1 millisecond (which is usually less than a few microseconds in intended applications), a small portion of each received frequency component should be ignored. Yes, the receiver can easily miss it.

The entire process of receiving nine frequency components may be repeated in additional 9 ms blocks of reception to increase processing gain. With a total receive time of 1 second, there would be approximately 111 such 9 ms blocks available for processing gain. Additionally, within each block there will be additional processing gain available from the main peak of 0.009/(2/Δf)≈383.

It is worth noting that in general signal reconstruction can be done very efficiently, essentially allowing all possible processing gains. For each of the 2N+3 received frequencies,
1. The phase and amplitude of each 1 millisecond reception of that frequency are measured to form a series of stored vectors (phasors) corresponding to that frequency.
2. Average the vectors stored for that frequency.
3. Finally, one period of the baseband signal with period 2/Δf is reconstructed using 2N+3 vector averages over 2N+3 frequencies and the reconstruction is used to estimate the signal TOA.

This method is not limited to 1 millisecond transmissions, and the length of transmissions may be increased or decreased. However, the total time for all transmissions must be short enough to stop any movement of the receiver or transmitter.

By simply reversing the polarity of the canceling function g(t), we obtain cancellation on alternate half-cycles of r(t) so that s( Cancellation between peaks of t) is possible. However, in order to obtain all peak-to-peak cancellation of s(t), the function g(t) and its polarity reversal must be applied to the receiver, which has the coefficient Includes weighting.

Coefficient weighting at the receiver. If desired, the coefficients b _k in equation (21) may be used for the construction of r(t) at the transmitter and instead introduced at the receiver. This is easily seen by considering the sequence of signals in equation (20), where the final signal is the same if _bk is introduced at the last step instead of at the beginning. Ignoring noise, the values are:

cosω _k t (at the baseband in the transmitter)
cos(ω+ω _k )t (transformed by frequency ω up to RF)
a _j cos[(ω+ω _k )(t−τ _j )+φ _j ] (at the receiver antenna)
a _j cos[ω _k (t−τ _j )+φ _j +θ] (translated by frequency −ω to baseband)
a _j b _k cos[ω _k (t−τ _j )+φ _j +θ] (weighted at baseband by factor bk)
(24)

The transmitter can then transmit all frequencies with the same amplitude, which simplifies its design. Note that this method also weights the noise at each frequency and its effect should be considered. Note also that coefficient weighting should be done at the receiver to effect a polarity reversal of g(t) to obtain twice the dominant peak available.

Scaling of Δf to the center frequency in the channel. Channelized transmission with constant channel spacing is required to meet FCC requirements at VHF or lower frequencies. For channelized transmission bands with small constant channel spacing compared to the overall allocated band, which is the case for VHF and lower frequency band(s), small adjustments to Δf may be necessary , allowing all transmitted frequencies to be centered on the channel without substantially changing performance from the original design. In the two examples of baseband signals presented previously, all frequency components are a plurality of Δf/2, so if the channel spacing divides Δf/2, the lowest RF transmitted frequency may be centered within one channel, and every other frequency may be centered in those channels.

In some radio frequency (RF) based identifications, in addition to the tracking and location system performing range finding functions, both the master unit and the tag unit also perform voice, data and control communication functions. . Similarly, in preferred embodiments, both the master unit and the tag perform voice, data and control communication functions in addition to range finding functions.

According to a preferred embodiment, the ranging signal(s) are subject to a wide range of advanced signal processing techniques, including multipath mitigation. However, these techniques may not be suitable for voice, data, and control signals. As a result, the operating range of the proposed system (as well as other existing systems) is limited by the range during voice and/or data and/or control communications, not by its ability to reliably and accurately measure distance. Being outside can be limited.

Other radio frequency (RF)-based identification, tracking, and location systems separate the ranging function from the voice, data, and control communication functions. In these systems separate RF transceivers are used to perform voice, data and control communication functions. The drawback of this approach is the increased cost, complexity, size, etc. of the system.

To avoid the drawbacks mentioned above, in a preferred embodiment several individual frequency components of the narrowband ranging signal or the baseband narrowband ranging signal are controlled using the same data/control signal and in the case of speech. is modulated using digitized voice packet data. At the receiver, the individual frequency components with the highest signal strength are demodulated, and the reliability of the information obtained is further enhanced by performing "voting" or other signal processing techniques that exploit information redundancy. obtain.

This method results in a "null" phenomenon in which incoming RF signals from multiple paths are destructively combined with the DLOS paths and each other, thus significantly reducing the received signal strength and its associated SNR. make it possible to avoid Moreover, such a method provides a set of frequencies at which incoming signals from multiple paths are destructively combined with the DLOS paths and with each other, and thus the received signal strength and associated with it. It allows finding frequencies that increase the SNR obtained.

As mentioned above, spectral estimation-based super-resolution algorithms generally use the same model: complex exponentials of frequencies and linear combinations of their complex amplitudes. This complex amplitude is given by Equation 3 above.

All spectral estimation-based super-resolution algorithms require prior knowledge of the number of complex exponents, ie, the number of passes in the multipath. This number of complex exponents is called the model size and is determined by the number of multipath components L as shown in equations 1-3. However, this information is not available when estimating path delays, which is the case for RF tracking-location applications. This adds another dimension to the spectral estimation process, namely estimation of model size, by means of super-resolution algorithms.

In the case of model size underestimation, the accuracy of frequency estimation is affected, and when the model size is overestimated, algorithms have been shown to generate unwanted, e.g., non-existent frequencies (non- Patent document 3). Existing methods of model size estimation, such as AIC (Akaike Information Criterion), MDL (Minimum Description Length), etc., have high sensitivity to correlations between signals (complex exponentials). However, in the case of RF multipath, this is always the case. Moreover, there is always a residual amount of correlation, eg, after a forward-backward smoothing algorithm has been applied.

[3] document uses an overestimated model to distinguish real frequencies (signals) from unwanted frequencies (signals) by estimating their signal power (amplitude), and then It has been proposed to reject signals with very low power. This method is an improvement over existing methods, but is not guaranteed. We implemented the method of [3] to simulate more complex cases with larger model sizes. It has been observed that in some cases the unwanted signal can have an amplitude very close to the actual signal amplitude.

All spectral estimation-based super-resolution algorithms work by separating the complex amplitude data of the incoming signal into two subspaces: the noise subspace and the signal subspace. If these subspaces are properly defined (separated), the model size is equal to the signal subspace size (dimension).

In one embodiment, model size estimation is accomplished using the "F" statistic. For example, for the ESPRIT algorithm, the singular value decompositions of the covariance matrix estimates (using forward/backward correlation smoothing) are ordered in ascending order. A division is then performed whereby the (n+1) eigenvalues are divided by the nth eigenvalue. This rate is an "F" random variable. The worst case is an 'F' random variable with (1,1) degrees of freedom. The 95% confidence interval for an “F” random variable with (1,1) degrees of freedom is 161. Setting that value as a threshold determines the model size. Also note that for the noise subspace, the eigenvalues represent an estimate of the noise power.

This method of applying the 'F' statistic to the rate of eigenvalues is a more accurate method of estimating model size. Note that other degrees of freedom in the 'F' statistic can also be used for threshold calculation and consequently model size estimation.

Nevertheless, in some cases, two or more very closely spaced (in time) signals may degenerate into one signal due to real-world measurement imperfections. As a result, the method described above underestimates the number of signals, ie the model size. Underestimating the model size reduces the accuracy of frequency estimation, so it is advisable to increase the model size by adding a constant number. This number can be determined experimentally and/or from simulations. However, when the signals are not closely spaced, the model size is overestimated.

In such cases, unwanted or nonexistent frequencies may appear. As mentioned above, using signal amplitude for unwanted signal detection does not always work. This is because in some cases it has been observed that the unwanted signal(s) have amplitudes very close to the actual signal(s) amplitude. Therefore, in addition to amplitude discrimination, filters can be implemented to improve the likelihood of removing unwanted frequencies.

The frequency estimated by the super-resolution algorithm is the artificial frequency (equation 2). In effect, these frequencies are individual path delays in a multipath environment. As a result, there should be no negative frequencies, and all negative frequencies produced by the super-resolution algorithm are unwanted frequencies that are rejected.

値から推定され得る。これらの方法は、より低い正確性を有するものの、このアプローチは、遅延、すなわち周波数を弁別するために使用される範囲を確立する。例えば、信号振幅

が最大に近い、すなわち、ヌルを避ける、Δｆ間隔における

の率は、ＤＬＯＳ遅延範囲を提供する。実際のＤＬＯＳ遅延は、２時間以上またはそれ以下までであり得るが、これは、不要な結果を拒否するのに役立つ範囲を定義する。 Furthermore, the DLOS distance range is the complex amplitude

can be estimated from the values. Although these methods have lower accuracy, this approach establishes the range used to discriminate between delays, ie frequencies. For example, signal amplitude

is close to the maximum, i.e. avoid nulls, in the Δf interval

A ratio of λ provides the DLOS delay range. Actual DLOS delays can be up to two hours or more or less, but this defines a useful range for rejecting unwanted results.

In an embodiment, the ranging signal makes round trips. In other words, it moves in both directions, ie from master/reader to target/slave and from target/slave back to master/reader.

The master transmits sound, ie α×e ^−jωt . where ω is the operating frequency in the operating band and α is the sound signal amplitude.

At the receiver of interest, the received signal (one way) is:

（２５）

(25)

where N is the number of signal paths in the multipath environment, K0 and _τ0 are the amplitude and time-of-flight of the DLOS signal, | _K0 |=1, _K0 >0, | _Km≠0 |≦1 and K _m≠0 can be positive or negative.

（２６）

(26)

は、周波数領域における一方向マルチパスＲＦチャネル伝達関数であり、Ａ（ω）≧０である。 here,

is the unidirectional multipath RF channel transfer function in the frequency domain, with A(ω)≧0.

The subject retransmits the received signal.

（２７）

(27)

または、

（２８）
である。 At the master receiver, the roundtrip signal is

or,

(28)
is.

（２９） On the other hand, from equations (26) and (28),

(29)

は、周波数領域におけるラウンドトリップマルチパスＲＦチャネル伝達関数である。 here,

is the round-trip multipath RF channel transfer function in the frequency domain.

は、これらのパス遅延の組み合わせ、例えば、τ_０＋τ_１、τ_０＋τ_２…、τ_１＋τ_２、τ_１＋τ_３，…等を含むからである。 From Equation 29, a round-trip multipath channel has a greater number of paths than a unidirectional channel multipath. Because, in addition to the τ ₀ ÷ τ _N path delays, the expression

contains combinations of these path delays, eg, τ ₀ +τ ₁ , τ ₀ +τ _{2 .} . . , τ ₁ +τ ₂ , τ ₁ +τ ₃ , .

These combinations dramatically increase the number of signals (complex exponents). Hence, the probability of very closely spaced (in time) signals also increases, which can lead to a significant underestimation of the model size. Therefore, it is desirable to obtain the unidirectional multipath RF channel transfer function.

が、対象／スレーブデバイスから直接的に取得可能である。しかしながら、一方向位相値

は、直接的に測定されることができない。ラウンドトリップ位相測定観測から一方向の位相を決定することが可能であり、すなわち、

及び

である。 In a preferred embodiment, the unidirectional amplitude value

can be obtained directly from the target/slave device. However, the one-way phase value

cannot be measured directly. It is possible to determine the phase in one direction from round-trip phase measurement observations, i.e.

as well as

is.

であるように、位相α（ω）の２つの値が存在する。 However, for each value of ω,

There are two values of phase α(ω) such that .

A detailed description that clears up this ambiguity is provided below. If the different frequency components of the ranging signal are close to each other, for the most part the unidirectional phase can be found by dividing the round-trip phase by two. The exception is phase, which includes regions near "nulls" where even small frequency steps can undergo significant changes. A "null" phenomenon is when incoming RF signals from multiple paths destructively combine with the DLOS paths and each other, thus significantly reducing the received signal strength and its associated SNR. Note

（３０）
であり、
ここで、Ａ（ω）≧０は大きさであり、α（ω）は、伝達関数の位相である。一方向インパルス応答が、それが受信されるのと同じチャネルを通して再送されて戻される場合、結果として生じる二方向伝達関数は、

（３１）
であり、
ここで、Ｂ（ω）≧０である。二方向伝達関数Ｇ（ω）は、いくつかの開いた周波数区間（ω_１，ω_２）内の全てのωについて、既知であると想定する。ｇ（ω）を生成した（ω_１，ω_２）上で定義される一方向伝達関数Ｈ（ω）を決定することが可能である？ Let h(t) be the one-way impulse response of the communication channel. The corresponding transfer function in the frequency domain is

(30)
and
where A(ω)≧0 is the magnitude and α(ω) is the phase of the transfer function. If the one-way impulse response is retransmitted back through the same channel in which it was received, the resulting two-way transfer function is

(31)
and
where B(ω)≧0. The bidirectional transfer function G(ω) is assumed to be known for all ω within some open frequency interval (ω ₁ , ω ₂ ). Is it possible to determine the one-way transfer function H(ω) defined above (ω ₁ , ω ₂ ) that produced g(ω)?

（３２）
であることは明確である。 Since the magnitude of the two-way transfer function is the square of the one-way magnitude,

(32)
It is clear that

（３３）
であるように、位相α（ω）の２つの値が存在する。 However, in attempting to find the phase of the one-way transfer function from observations of G(ω), the situation is more elusive. For each value of ω,

(33)
There are two values of phase α(ω) such that .

A number of different solutions can be generated independently by choosing one of two possible phase values for each different frequency ω.

The following theorem, which assumes that any one-way transfer function is continuous at all frequencies, helps to resolve this situation.

のゼロを含まない周波数ωの開いた区間とする。

をＩ上の連続関数とし、ここで、β（ω）＝２γ（ω）である。次いで、Ｊ（ω）及び－Ｊ（ω）は、Ｉ上でＧ（ω）を生成する一方向伝達関数であり、他は存在しない。 Theorem 1 Let I be the two-way transfer function

be an open interval of the frequency ω that does not contain the zero of

be a continuous function on I, where β(ω)=2γ(ω). Then J(ω) and −J(ω) are the one-way transfer functions that produce G(ω) on I and the others do not exist.

であり、それは、Ｉ上で可微分であるので、Ｉ上で連続的であり、ここでβ（ω）＝２α（ω）である。Ｉ上でＧ（ω）≠０であるので、Ｈ（ω）及びＪ（ω）は、Ｉ上でゼロではない。次いで、

（３４） Proof One of the solutions for the one-way transfer function is the function

, which is differentiable on I and therefore continuous on I, where β(ω)=2α(ω). H(ω) and J(ω) are non-zero on I because G(ω)≠0 on I. then

(34)

Since H(ω) and J(ω) are continuous on I and not zero, their ratio is continuous on I, so the right-hand side of (34) is is continuous with The condition β(ω)=2α(ω)=2γ(ω) implies that for each ω∈I, α(ω)−γ(ω) is either 0 or π. However, α(ω)−γ(ω) cannot be converted between these two values without introducing a discontinuity on the right-hand side of (34). Therefore, either α(ω)−γ(ω)=0 for all ωεI or α(ω)−γ(ω)=π for all ωεI. In the first case we have J(ω)=H(ω) and in the second we have J(ω)=−H(ω).

のゼロを含まない任意の開いた区間Ｉ上で一方向解を得ることを証明する。我々は、関数

を形成し、Ｊ（ω）を連続的にさせるようにβ（ω）＝２γ（ω）を満たすγ（ω）の値を選択する。この特性を有する解、すなわち、Ｈ（ω）が存在することが知られているので、これを行うことは常に可能である。 This theorem states that the transfer function

We prove that we obtain a one-way solution on any open interval I that does not contain zero of . we have the function

and choose a value of γ(ω) that satisfies β(ω)=2γ(ω) to make J(ω) continuous. It is always possible to do this because it is known that there exists a solution with this property, namely H(ω).

An alternative procedure for finding a one-way solution is based on the following theorem.

を一方向伝達関数とし、ＩをＨ（ω）のゼロを含まない周波数ωの開いた区間とする。次いで、Ｈ（ω）の位相関数α（ω）は、Ｉ上で連続的である必要がある。 Theorem 2

Let be the one-way transfer function and let I be the open interval of frequency ω that does not contain a zero of H(ω). Then the phase function α(ω) of H(ω) must be continuous on I.

であることが分かる。ε＞０が任意に選択されたので、我々は、位相関数α（ω）がω_０において連続的であるように、ω→ω_０の際にα（ω）→α（ω_０）であると結論付ける。 Proof Let ω ₀ be the frequency in interval I. In FIG. 7 the complex value H(ω ₀ ) is plotted as a point in the complex plane and with the hypothesis that H(ω ₀ )≠0. Let ε>0 be any small real number, and consider the two angles ε shown in FIG. 7 and the circles centered at and tangent to the two lines OA and OB. By assumption, H(ω) is continuous for all ω. Therefore, if ω is sufficiently close to ω ₀ , the complex value H(ω) lies within the circle,

It turns out that Since ε>0 was arbitrarily chosen, we have α(ω)→α(ω ₀ ) as ω→ω ₀ such that the phase function α(ω) is continuous at ω ₀ conclude.

のゼロを含まない周波数ωの開いた区間とする。

をＩ上の関数とし、ここで、β（ω）＝２γ（ω）であり、γ（ω）はＩ上で連続的である。次いで、Ｊ（ω）及び－Ｊ（ω）は、Ｉ上でＧ（ω）を生成する一方向伝達関数であり、他は存在しない。 Theorem 3 Let I be the two-way transfer function

be an open interval of the frequency ω that does not contain the zero of

be a function on I, where β(ω)=2γ(ω) and γ(ω) is continuous on I. Then J(ω) and −J(ω) are the one-way transfer functions that produce G(ω) on I and the others do not exist.

であることを知っており、ここで、β（ω）＝２α（ω）である。Ｉ上でＧ（ω）≠０であるので、Ｈ（ω）及びＪ（ω）は、Ｉ上でゼロではない。次いで、

（３５） Proof This proof is similar to the proof of Theorem 1. We find that one of the solutions for the one-way transfer function is the function

where β(ω)=2α(ω). H(ω) and J(ω) are non-zero on I because G(ω)≠0 on I. then

(35)

By hypothesis, γ(ω) is continuous on I, and by Theorem 2, α(ω) is also continuous on I. Therefore α(ω)−γ(ω) is continuous on I. The condition β(ω)=2α(ω)=2γα(ω) implies that for each ω∈I, α(ω)−γ(ω) is either 0 or π. However, α(ω)-γ(ω) cannot be converted between these two values without a discontinuity on I. Therefore, either α(ω)−γ(ω)=0 for all ωεI or α(ω)−γ(ω)=π for all ωεI. In the first case we have J(ω)=H(ω) and in the second we have J(ω)=−H(ω).

のゼロを含まない任意の開いた区間Ｉ上で一方向解を得ることを我々に示し、我々は、単純に関数

を形成し、位相関数γ（ω）を連続的にさせるようにβ（ω）＝２γα（ω）を満たすγ（ω）の値を選択する。この特性を有する解、すなわちＨ（ω）が存在することが知られているので、常に、これを行うことが可能である。 Theorem 3 states that the transfer function

We show that we obtain a one-way solution on any open interval I that does not contain zero of , and we simply write the function

and choose a value of γ(ω) that satisfies β(ω)=2γα(ω) to make the phase function γ(ω) continuous. It is always possible to do this because it is known that there exists a solution with this property, namely H(ω).

The theorem above shows how to reconstruct the two one-way transfer functions that generate the two-way function G(ω), but only on the zero-free frequency interval I of G(ω). Useful. In general, G(ω) is observed over the frequency interval (ω ₁ , ω ₂ ), which may contain zeros. The following is a method that can circumvent this problem, requiring that there are only a finite number of zeros of G(ω) at (ω ₁ , ω ₂ ) and that the one-way transfer function is (ω ₁ , ω ₂ ) Suppose we have derivatives of all orders above, not all of them vanishing at any given frequency ω.

Let H(ω) be a one-way function producing G(ω) on the interval (ω ₁ , ω ₂ ), and let G(ω) have at least one zero on (ω ₁ , ω ₂ ). Assume. The zeros in G(ω) separate (ω ₁ , ω ₂ ) into a finite number of open adjacent frequency intervals J ₁ , J ₂ , . . . , J _n . On each such interval, a solution H(ω) or −H(ω) is found using either Theorem 1 or Theorem 3. These solutions need to be "transformed together" so that the transformed solution is either H(ω) or -H(ω) over all of (ω ₁ , ω ₂ ). To do this, we set the We need to know how to pair the solutions in two adjacent subintervals.

We illustrate the diversion procedure starting with the first two open adjacent sub-intervals _J1 and _J2 . These subintervals are adjacent at frequency _ω1 , which is the zero of G(ω) (of course, _ω1 is not contained within any subinterval). By our above assumptions about the properties of the one-way transfer function, there must be a smallest positive integer n such that H ⁽ⁿ⁾ (ω ₁ )≠0, where the superscript (n) is , denotes the nth derivative. Then, as ω→ _ω1 from the left, the limit of the n-th derivative of our one-way solution in _J1 is determined whether our solution in _J1 is H(ω) or −H(ω) , either H ⁽ⁿ⁾ (ω ₁ ) or -H ⁽ⁿ⁾ (ω ₁ ). Similarly, as ω→ _ω1 from the right, the limit of the nth derivative of our one-way solution in _J2 is that our solution in _J2 is −H(ω) or −H(ω) , either H ⁽ⁿ⁾ (ω ₁ ) or -H ⁽ⁿ⁾ (ω ₁ ). Since H ⁽ⁿ⁾ (ω ₁ ) ≠ 0, the two limits are if and only if the solutions in J ₁ and J ₂ are both H(ω) or both −H(ω) , will be equal to If the left and right limits are not equal, we flip the solution in subinterval _J2 . Otherwise, do not invert.

After flipping the solution in sub-interval _J2 (optionally), we do the same procedure for sub-intervals _J2 and _J3 , flipping the solution in sub-interval _J3 (optionally) do. Continuing in this way, we finally construct a complete solution on the interval (ω ₁ , ω ₂ ).

It would be desirable if higher derivatives of H(ω) were not required in the reconstruction procedure. because they are difficult to compute accurately in the presence of noise. This problem is unlikely. Because at any zero of G(ω), the first derivative of H(ω) is very likely non-zero, otherwise the second derivative is very likely non-zero. This is because

In a practical manner, the two-way transfer function G(ω) is measured at discrete frequencies, which are combined to allow fairly accurate computation of the near-zero derivative of G(ω). Must be close enough.

For RF-based ranging, there is a need to resolve closely spaced, overlapping, and noisy unknown echoes of a ranging signal with a priori known shape. Assuming that the ranging signal is narrowband, in the frequency domain this RF phenomenon can be described as the sum of several sinusoids for each multipath component and with the complex attenuation and propagation delay of the path, respectively ( modeled).

Taking the sum Fourier transform described above expresses this multipath model in the time domain. Swapping the roles of time and frequency variables in this time domain representation, this multipath model becomes a harmonic signal spectrum, in which the delay propagation of paths is transformed into harmonic signals.

Ultra (high) resolution spectral estimation methods are designed to distinguish closely located frequencies in the spectrum and are used to estimate individual frequencies, e.g. path delays, of multiple harmonic signals. As a result, path delays can be accurately estimated.

Super-resolution spectral estimation uses the eigenstructure of the covariance matrix of the baseband ranging signal samples and the eigenproperties of the covariance matrix to provide a solution to the underlying estimation of individual frequencies, eg, path delays. One of the eigenstructural properties is that the eigenvalues can be combined and consequently partitioned into orthogonal noise and signal eigenvectors, aka subspaces. Another inherent structural property is the rotation-invariant signal subspace property.

Subspace decomposition techniques (MUSIC, rootMUSIC, ESPRIT, etc.) rely on splitting the estimated covariance matrix of the observed data into two orthogonal subspaces, the noise subspace and the signal subspace. The theory behind the subspace decomposition methodology is that the projection of observables onto the noise subspace consists only of noise, and the projection of observables onto the signal subspace consists of only signal.

The spectral estimation method assumes that the signal is narrowband and that the number of harmonic signals is also known, ie the size of the signal subspace must be known. The size of the signal subspace is called the model size. In general it is not well known and can change rapidly as the environment changes, especially indoors. One of the most difficult and intractable problems when applying any subspace decomposition algorithm is the dimension of the signal subspace, which can be viewed as the number of frequency components present, which is the direct path plus is the number of multipath reflections. Due to real-world measurement imperfections, there is always an error in model size estimation, which in turn results in a loss of frequency estimation, ie range accuracy.

To improve the accuracy of range measurements, one embodiment includes six features that develop a state-of-the-art methodology for subspace-resolved high-resolution estimation. Combining two or more algorithms that estimate individual frequencies by using different eigenstructure properties that further reduce delay path determination ambiguity is included.

Root Music finds the individual frequencies that minimize the energy of the projection when the observable is projected onto the noise subspace. The ESPRIT algorithm determines individual frequencies from the rotation operator. Moreover, in many respects, this operation is the conjugate of Music in that it finds the frequencies that maximize the energy of the projection when the observables are projected onto the signal subspace.

Model size is key to both of these algorithms, and in practice, in complex signal environments, such as those found in indoor ranging, the model size that provides the best performance for Music and ESPRIT is They are generally not equal, for reasons described below.

For Music, it is desirable to over-identify the basic elements of the decomposition as "signal eigenvalues" (type I error). This minimizes the amount of signal energy projected onto the noise subspace and improves accuracy. For ESPRIT, the opposite is true: it is desirable to over-identify the fundamental elements of the decomposition as "noise eigenvalues". This is again a type 1 error. This minimizes the effect of noise on the energy projected onto the signal subspace. Therefore, the model size for Music is generally somewhat larger than for ESPRIT.

Second, in complex signal environments, due to strong reflections and the possibility that the direct path is actually much weaker than some of the multipath reflections, the model size cannot be estimated with sufficient statistical reliability. There are cases where it is difficult to This problem processes observable data using Music and ESPRIT by estimating a "base" model size for both Music and ESPRIT, and within a window of model sizes defined by the base model size for each. dealt with by This results in multiple measurements for each measurement.

A first feature of the embodiments is the use of the F-statistic to estimate the model size (see above). A second feature is the use of different type I error probabilities in the F-statistics for Music and ESPRIT. This implements a type 1 excess error between Music and ESPRIT as described above. A third feature is the use of base model sizes and windows to maximize the probability of finding direct paths.

Due to the potentially rapidly changing physical and electronic environment, not all measurements provide robust answers. This is addressed by using cluster analysis on multiple measurements to provide robust range estimates. A fourth feature of embodiments is the use of multiple measurements.

Since there are multiple signals, using multiple model sizes from both the Music and ESPRIT implementations respectively, the probability distributions of the multiple answers resulting from multiple measurements are multimodal. Conventional cluster analysis is not sufficient for this application. A fifth feature is the development of multimodal cluster analysis for estimating equivalent ranges of direct and reflected multipath components. A sixth feature is the analysis of the range estimate statistics provided by cluster analysis (range and standard deviation, and combinations of those estimates that are statistically identical. This results in more accurate range estimates. bring as

The methods described above may also be used in wide bandwidth ranging signal location systems.

（Ａ１）
を取得する。 For the derivation of r(t) in the threshold method, starting with equation (20), we have

(A1)
to get

が使用される。 where the trigonometric identities

is used.

Except for a ₀ , the coefficients a _k are zero for even k. The reason for this is that on the interval I, the function 1/sinπΔft that we are trying to approximate by h(t) is even about the center of I, but for odd k, k≠0, the basis functions sink πΔft is odd about the center of I and is therefore orthogonal to 1/sin πΔft on I. Therefore, we can make k=2n+1 permutations, let M be an odd positive integer. In practice, we take M=2N+1. This choice has been experimentally determined to provide a substantial amount of vibration cancellation in interval I.

（Ａ２）

(A2)

（Ａ３）
を取得する。 where we make the permutation k=N−n in the first addition and the permutation k=N+n+1 in the second addition,

(A3)
to get

（Ａ４）
を結果としてもたらす。 The subtraction of g(t) from s(t) is

(A4)
results in

here,
b ₀ =1-(1/2)a _2N+1
b _k =2−(1/2)a _2(N−k)+1 for k=1, 2, . . . , N b _k =−(1/2)a _2(k−N)−1 k=N+1 , N+2, . . . , 2N+1, c=-a ₀
(A5)
and

（Ａ６）
として書かれ得る。 Then (A4) is

(A6)
can be written as

The present embodiments relate to positioning/localization methods in wireless communications and other wireless networks that substantially obviate one or more of the shortcomings of the related art. The present embodiments advantageously improve the accuracy of tracking and location functions in multiple types of wireless networks by utilizing the multipath mitigation processes, techniques and algorithms described in US Pat. These wireless networks are wireless personal area networks (WPGAN), such as ZigBee and Blue Tooth®, wireless local area networks (WLAN), such as WiFi and UWB, and wireless metropolitan areas that typically consist of multiple WLANs. Area Networks (WMAN), of which WiMax is a prime example, Wireless Wide Area Networks (WAN), such as white space TV bands, and Mobile Device Networks (MDN), typically used to transmit voice and data. )including. MDN is typically based on the Global System for Mobile Communications (GSM) and Personal Communications Service (PCS) standards. The latest MDN is based on the Long Term Evolution (LTE) standard. These wireless networks typically include base stations, desktop, tablet and laptop computers, handsets, smartphones, actuators, specialized tags, sensors, and other communication and data devices (generally all of these devices are , referred to as “wireless network devices”).

Existing location and positioning information solutions use multiple technologies and networks, including GPS, AGPS, cell tower triangulation, and Wi-Fi. Some of the methods used to derive this location information include RF fingerprinting, RSSI, and TDOA. While acceptable for current E911 requirements, existing localization and ranging methods are not reliable and Not accurate.

The method described in US Pat. No. 6,200,301 significantly improves the ability to accurately locate and track a target device within a single wireless network or a combination of multiple wireless networks. Embodiments are used by wireless networks that use Enhanced Cell-ID and OTDOA (Observed Time Difference of Arrival), including DL-OTDOA (Downlink OTDOA), U-TDOA, UL-TDOA and others It is a significant improvement over existing implementations of tracking and localization methods.

Cell-ID location techniques allow estimation of the location of a user (UE-user equipment) with the accuracy of specific sector coverage. Therefore, the achievable accuracy depends on the cell (base station) sectorization scheme and antenna beam width. To improve accuracy, the Enhanced Cell ID technique adds RTT (Round Trip Time) measurements from the eNB. Here, RTT constitutes the difference between the transmission of a downlink DPCH—Dedicated Physical Channel, (DPDCH)/DPCCH: Dedicated Physical Data Channel/Dedicated Physical Control Channel) frame and the start of the corresponding uplink physical frame. Note that In this example, the frame(s) described above serve as the ranging signal. Based on the information how far this signal travels from the eNB to the UE, the distance from the eNB can be calculated (see Figure 10).

The Observed Time Difference of Arrival (OTDOA) technique calculates the time of arrival of signals coming from neighboring base stations (eNBs). UE position can be estimated at the handset (UE-based method) or at the network (NT-based UE-assisted method) once signals are received from three base stations. The signal to be measured is the CPICH (Common Pilot Channel). The signal propagation time is correlated to the locally generated replicas. The correlation peak indicates the observed time of propagation of the measured signal. The time difference of arrival values between two base stations determine a hyperbola. At least three reference points are required to define two hyperbolas. The UE location is at the intersection of these two hyperbolas (see Figure 11).

An idle period downlink (IPDL) further enhances OTDOA. The OTDOA-IPDL technique is based on the same measurements that normal OTDOA time measurements are made during periods of inactivity, in which the serving eNB has finished its transmission and a UE within the coverage of this cell Allows listening to pilots coming from(s). The serving eNB provides periods of inactivity in continuous or burst mode. In continuous mode, one period of inactivity is inserted every downlink physical frame (10 ms). In burst mode, periods of inactivity occur pseudorandomly. A further improvement is obtained with time-aligned IPDL (TA-IPDL). Time alignment creates a common period of inactivity during which each base station terminates its transmission or transmits a common pilot. Pilot signal measurements are taken during periods of inactivity. There are some other techniques that can further enhance the DL OTDOA-IPDL method, eg Cumulative Virtual Blanking, UTDOA (Uplink TDOA), etc. All of these techniques improve the ability to listen to other (non-serving) eNB(s).

One significant drawback of the OTDOA-based technique is that the base station timing relationship needs to be known or measured (synchronized) for the method to be viable. For asynchronous UMTS networks, the 3GPP standard proposes how this timing can be recovered. However, network operators have not implemented such solutions. As a result, alternatives have been proposed to use RTT measurements instead of CPICH signal measurements (see US Pat. No. 6,300,003, John Carlson et al., SYSTEM AND METHOD FOR NETWORK TIMING RECOVERY IN COMMUNICATIONS NETWORKS).

All of the methods/techniques described above are based on terrestrial signal time-of-arrival and/or time-of-arrival measurements (RTT, CPICH, etc.). A problem with such measurements is that they are severely affected by multipath. This, in turn, significantly reduces the location/tracking accuracy of the methods/techniques described above (see Non-Patent Document 4).

One multipath mitigation technique uses detection/measurement from an excess number of eNB(s) or radio base stations (RBS). The minimum number is 3, but for multipath mitigation, the number of RBSs required is at least 6-8 (US Pat. A LTE (LONG TERM EVOLUTION) WIRELESS COMMUNICATIONS SYSTEM). However, the probability that a UE will hear from this large number of eNB(s) is much lower than from three eNB(s). This is because with a large number of RBSs (eNBs) there may be some far away from the UE and the received signal from these RBS(s) may be below the UE receiver sensitivity level, or This is because the received signal has a low SNR.

In the case of RF reflections (eg, multipath), multiple copies of the RF signal with different delay times are superimposed on the DLOS (direct line of sight) signal. Since the CPICH, uplink DPCCH/DPDCH, and other signals used for various Cell-ID and OTDOA methods/techniques, including RTT measurements, are of limited bandwidth, the DLOS and reflected signals are Without proper multipath processing/mitigation, these reflected signals cannot be distinguished without proper multipath processing/mitigation and, moreover, without this multipath processing, these reflected signals are estimated time difference of arrival (TDOA) and time of arrival ( TOA) induce an error in the measurement.

For example, 3G TS25.515v. The 3.0.0 (199-10) standard defines RTT as "...the transmission of a downlink DPCH frame (signal) and the start of the corresponding uplink DPCCH/DPDCH frame (signal) from the UE (the first significant path) is defined as the "difference between The standard does not define what constitutes this "first significant path". The standard continues to note that "the definition of the first significant path needs further elaboration". For example, in severe multipath environments it is a common occurrence that the DLOS signal, the first significant path , is severely attenuated compared to one or more reflected signal(s). (10dB-20dB). If the "first significant path" is determined by a signal strength measurement, it may be one of the reflected signal(s) and not the DLOS signal. This results in erroneous TOA/DTOA/RTT measurement(s) and compromised location accuracy.

In previous generations of wireless networks, location accuracy was also affected by the low sampling rate of the frames (signals) used by the location methods, ie RTT, CPCIH and other signals. Current 3rd and subsequent wireless network generations have significantly higher sampling rates. As a result, in these networks the real impact of location accuracy comes from the terrestrial RF propagation phenomenon (multipath).

Embodiments may be used in all wireless networks that utilize reference and/or pilot signals and/or synchronization signals, including simplex, half-duplex, and full-duplex modes of operation. For example, embodiments operate with wireless networks that utilize OFDM modulation and/or derivatives thereof. Embodiments therefore operate with LTE networks.

It is also applicable to other wireless networks, including WiMax, WiFi, and whitespace. Other wireless networks that do not use reference and/or pilot or synchronization signals have the following types of alternative modulation embodiments as described in US Pat. is dedicated to the ranging signal/ranging signal element, 2) if the ranging signal element (US Pat. No. 3,800,000) is embedded in the transmitted/received signal frame(s), and 3) (as described in US Pat. One or more of the cases where the ranging signal element is embedded with the data may be utilized.

These alternative embodiments utilize the multipath mitigation processor and multipath mitigation techniques/algorithms described in US Pat.

Also, multiple wireless networks may simultaneously utilize the preferred and/or alternative embodiments. As an example, a smart phone may have Bluetooth, WiFi, GSM, and LTE capabilities with the ability to operate on multiple networks simultaneously. Depending on application requirements and/or network availability, different wireless networks may be utilized to provide positioning/location information.

The proposed embodiment methods and systems utilize wireless network reference/pilots and/or synchronization signals. Furthermore, reference/pilot signal/synchronization signal measurements may be combined with RTT (Round Trip Time) measurements or system timing. According to an embodiment, RF-based tracking and location is implemented over 3GPP LTE cellular networks, but other wireless networks such as WiMax, Wi-Fi, LTE, which utilize various signaling techniques. It can also be implemented on sensor networks and the like. Both the exemplary embodiment and the alternative embodiments described above utilize the multipath mitigation methods/techniques and algorithms described in US Pat. The proposed system can use digital signal processing implemented in software.

The system of embodiments leverages user equipment (UE), eg, mobile phones or smart phones, hardware/software as well as base station (NodeB)/enhanced base station (eNB) hardware/software. A base station generally consists of a transmitter and receiver in a shed or cabinet connected to an antenna by a feedline. These base stations include microcells, picocells, macrocells, umbrella cells, cell towers, routers, and femtocells. As a result, there is little or no incremental cost for the UE device and the overall system. At the same time, localization accuracy is significantly improved.

The accuracy improvement results from the multipath mitigation provided by this embodiment and US Pat. Embodiments use multipath mitigation algorithms, network reference/pilots and/or synchronization signals, and network nodes (eNBs). These can be supplemented with RTT (Round Time Trip) measurements. Multipath mitigation algorithms are implemented in the UE and/or the base station (eNB) or both the UE and the eNB.

Embodiments provide multipath mitigation processors/algorithms that enable separation of DLOS and reflected signals even when the DLOS signal is significantly attenuated (below 10-20 dB) compared to one or more reflected signals. (cf. US Pat. No. 5,300,002) are advantageously used. Embodiments therefore significantly reduce the estimated ranging signal DLOS time-of-flight and the resulting errors in the TOA, RTT, and DTOA measurements. The proposed multipath mitigation and DLOS discrimination (recognition) method can be used on all RF bands and wireless systems/networks. Furthermore, it can support various modulation/demodulation techniques, including spread spectrum techniques such as DSS (Direct Spread Spectrum) and FH (Frequency Hopping).

Additionally, noise reduction methods can be applied to further improve the accuracy of the method. These noise reduction methods may include, but are not limited to, coherent summing, incoherent summing, adaptive filtering, time diversity techniques, and the like. The residual multipath interference error can be further reduced by applying post-processing techniques such as maximum likelihood estimation (eg, Viterbi algorithm), minimum variance estimation (Kalman filter), and so on.

In this embodiment, the multipath mitigation processor and multipath mitigation techniques/algorithms do not alter the RTT, CPCIH, and other signals and/or frames. The present embodiments leverage wireless network references, pilots, and/or synchronization signals used to obtain channel response/estimation. The invention uses channel estimation statistics produced by the UE and/or eNB (see US Pat.

LTE networks use unique (non-data) reference/pilots and/or synchronization s-signals (known signals) that are transmitted in every downlink and uplink subframe and can span the entire cell bandwidth. For the sake of brevity, reference/pilot and synchronization signals will be referred to as reference signals hereinafter. An example of LTE reference signals is in FIG. 9 (these signals are interspersed between LTE resource elements). From FIG. 2, reference signals (symbols) are transmitted every 6 subcarriers. Furthermore, the reference signals (symbols) are shifted in both time and frequency. In total, the reference signal covers every third subcarrier.

These reference signals are used by the UE in initial cell search, downlink signal strength measurement, scheduling, handover, and so on. UE-specific reference signals for channel estimation (response determination) for coherent demodulation are included in the reference signals. In addition to the UE-specific reference signals, other reference signals may also be used for channel estimation purposes (see Chen et al., US Pat. No. 6,300,000).

LTE utilizes OFDM (Orthogonal Frequency Division Multiplexing) modulation (technique). In LTE, ISI (inter-symbol interference) caused by multipath is addressed by inserting a cyclic prefix (CP) at the beginning of each OFDM symbol. CP introduces enough delay so that the delayed reflected signal of the previous OFDM symbol vanishes before reaching the next OFDM symbol.

An OFDM symbol consists of multiple very closely spaced subcarriers. Inside an OFDM symbol, staggered copies of the current symbol (caused by multipath) result in inter-carrier interference (ICI). In LTE, ICI is addressed (mitigated) by determining the multipath channel response and by correcting the channel response at the receiver.

In LTE, the multipath channel response (estimate) is computed at the receiver from the subcarriers carrying the reference symbols. An interpolation method is used to estimate the channel response on the remaining subcarriers. The channel response is calculated (estimated) in the form of channel amplitude and phase. Once the channel response is determined (by periodic transmission of a known reference signal), multipath-induced channel distortion is mitigated by applying amplitude and phase shifts on a subcarrier-by-subcarrier basis. 5).

LTE multipath mitigation is designed to eliminate ISI and ICI (by cyclic prefix insertion), but not separate the DLOS signal from the reflected signal. For example, the time-shifted duplicates of the current symbol will spread the respective modulated subcarrier signals over time, thus causing ICI. Correction of the multipath channel response using the LTE techniques described above will eventually reduce the modulated subcarrier signal, but this type of correction will cause the resulting modulated subcarrier signal (inside the OFDM symbol) to be DLOS Not guaranteed to be a signal. If the DLOS modulated subcarrier signal is significantly attenuated compared to the delayed reflected signal(s), the resulting output signal will be the delayed reflected signal(s) and the DLOS signal will be lost. will be

In LTE compliant receivers, further signal processing includes DFT (Digital Fourier Transform). It is well known that the DFT technique(s) can only eliminate (remove) replicas of the signal(s) that are delayed for a time greater than or equal to the time inversely proportional to the signal and/or channel bandwidth. be. The accuracy of this method may be suitable for efficient data transfer, but it is not accurate enough for precise distance measurements in harsh multipath environments. For example, to achieve 30 meter accuracy, the signal and receiver channel bandwidth should be greater than or equal to ten megahertz (1/10 MHz=100 ns). For better accuracy, the signal and receiver channel bandwidth should be wider, 100 MHz for 3 meters.

However, CPICH, uplink DPCCH/DPDCH, and other signals used in various Cell-ID and OTDOA methods/techniques, including RTT measurements, and LTE received signal subcarriers have bandwidths significantly lower than 10 MHz. have. As a result, currently utilized methods/techniques (in LTE) produce location errors in a range of 100 meters.

To overcome the above limitations, embodiments use a unique combination of subspace-resolved high-resolution spectral estimation methodologies and implementations of multimodal cluster analysis. This analysis and related multipath mitigation methods/techniques and algorithms described in US Pat.

Compared to the methods/techniques used in LTE, in a severe multipath environment, this method/technique and algorithm (US2004/0020002) provides reliable and accurate DLOS path extraction from other multipath (MP) paths. A 20- to 50-fold improvement in accuracy in distance measurement is achieved with a good separation.

The method/technique and algorithm described in US Pat. Therefore, LTE reference signals used for channel estimation (response determination) and other reference signals (including pilots and/or synchronization signals) can also be used as ranging signals in the methods/techniques and algorithms described in US Pat. In this case, the ranging signal complex amplitude is the channel response calculated (estimated) by the LTE receiver in the form of amplitude and phase, in other words the channel response calculated (estimated) by the LTE receiver Response statistics can provide the complex amplitude information required by the methods/techniques and algorithms described in US Pat.

In an ideal open-space RF propagation environment without multipath, the phase change of the received signal (ranging signal), eg, the channel response phase, is directly proportional to the frequency of the signal (linear). RF signal time-of-flight (propagation delay) in such environments can be computed directly from the phase dependence on frequency by computing the first derivative of the phase dependence on frequency. The result is the propagation delay constant.

In this ideal environment, the absolute phase value at the initial (or any) frequency is irrelevant, because the derivative is unaffected by the phase absolute value.

In severe multipath environments, the phase change with frequency of the received signal is a complex curve (non-linear) and the first derivative provides information that can be used for accurate separation of the DLOS path from other reflected signal paths. do not provide This is the reason for utilizing the multipath mitigation processor and method(s)/techniques and algorithms described in US Pat.

If the phase and frequency synchronization (phase coherence) achieved in a given wireless network/system is very good, the multipath mitigation processor and method(s)/techniques described in US Pat. As well, the algorithm accurately separates the DLOS path from other reflected signal paths to determine its DLOS path length (time of flight).

No additional measurements are required in this phase coherent network/system. In other words, unidirectional ranging (simplex ranging) can be achieved.

However, if the degree of synchronization (phase coherence) achieved in a given wireless network/system is not precise enough, then in severe multipath environments the phase and amplitude variation with frequency of the received signal may be 2 It can be very similar to measurements made at one or more different locations (distances). This phenomenon can lead to ambiguity in the DLOS range (time of flight) determination of the received signal.

To resolve this ambiguity, it is necessary to know the actual (absolute) phase value for at least one frequency.

However, the amplitude and phase dependence on frequency computed by the LTE receiver does not contain the actual phase values. This is because all amplitude and phase values are computed from the downlink/uplink reference signals relative to each other, for example. Therefore, the amplitude and phase of the channel response calculated (estimated) by the LTE receiver requires the actual phase values at at least one frequency (subcarrier frequency).

In LTE, this actual phase value is derived from one or more RTT measurement(s), TOA measurements, or from time stamping of one or more received reference signals provided that: 1) these signals are are also known at the receiver (or vice versa), 2) the receiver and eNB clocks are well synchronized in time, and/or 3) multilateration can be determined using techniques.

All of the above methods provide time-of-flight values for one or more reference signals. From the time-of-flight values and frequencies of these reference signals, the actual phase values at one or more frequencies can be calculated.

The present embodiments apply the multipath mitigation processor, method(s)/techniques and algorithms described in US Pat. or 2) the amplitude and phase dependence on frequency computed by the LTE UE and/or eNB receiver and the actual phase value(s) for one or more frequencies obtained via RTT and/or TOA. possible) and/or time-stamping measurements achieve highly accurate DLOS ranging/localization in severe multipath environments.

In these cases, the actual phase value(s) are affected by multipath. However, this does not affect the performance of the methods/techniques and algorithms described in US Pat.

In LTE RTT/TOA/TDOA/OTDOA, including DL-OTDOA, U-TDOA, UL-TDOA, etc., measurements can be performed with a resolution of 5 meters. RTT measurements are performed during dedicated connections. Therefore, multiple simultaneous measurements are possible when the UE is in handover and when the UE periodically collects and reports measurements back to the UE, during which DPCH frames are transmitted to the UE and different networks ( base station). Similar to RTT, TOA measurements provide the time-of-flight (propagation delay) of the signal, but TOA measurements cannot be made simultaneously [4].

To locate a UE on a plane, DLOS distances need to be determined from/to at least three eNB(s). In order to locate the UE in three-dimensional space, at least four DLOS distances from/to four eNB(s) are determined (assuming at least one eNB is not coplanar) need to be

An example of a UE positioning method is shown in FIG.

In case of very good synchronization no RTT measurement is required.

If the degree of synchronization is not accurate enough, methods such as OTDOA, Cell ID+RTT, and others, e.g., AOA (Angle of Arrival) and its combination with other methods, may be used for UE localization. can be used.

Cell ID + RTT Tracking - Accuracy of the location method is affected by multipath (RTT measurements) and eNB (base station) antenna beamwidth. The antenna beamwidth of the base station lies between 33 and 65 degrees. These wide beamwidths result in localization errors of 50-150 meters in metropolitan areas [4]. Given that the current LTE RTT ranging average error is about 100 meters in a severe multipath environment, the total expected average location error currently exploited by the LTE Cell ID+RTT method is about 150 meters.

One of the embodiments is the UE localization based AOA method, whereby one or more reference signals from the UE are used for UE localization purposes. It contains the AOA determination device location for determining the DLOS AOA. A device may be co-located with a base station and/or may be installed at one or more separate locations independent of the base station location. The coordinates of these locations are presumably known. No changes are required on the UE side.

This device includes a small antenna array and is based on variations of the same multipath mitigation processor, method(s)/techniques and algorithms described in US Pat. This one possible embodiment has the advantage of precise determination of the AOA of the DLOS RF energy from the UE unit (very narrow beamwidth).

In one alternative, this added device is a receive-only device. As a result, its size/weight and cost are very low.

Embodiments in which accurate DLOS range measurements are obtained combined with embodiments in which accurate DLOS AOA determinations can be made significantly improve the Cell ID + RTT Tracking-Location Method accuracy by a factor of 10 or more. Another advantage of this approach is that the UE location can be determined at any time with a single tower (not requiring the UE to be placed in soft handover mode). Accurate location determination can be obtained using a single tower, eliminating the need to synchronize multiple cell towers. Another option to determine the DLOS AOA is to use existing eNB antenna arrays and eNB equipment. This option may further lower the cost of implementing the improved Cell-ID+RTT method. However, since eNB antennas are not designed for location applications, positioning accuracy may be degraded. Also, the network operator may be unwilling to implement the requested changes in the base station (software/hardware).

LTE (Evolved Universal Terrestrial Radio Access (E-UTRA), Physical Channels and Modulations, 3GPP TS36.211 Release 9 Technical Specification) added Positioning Reference Signals (PRS). These signals are used by the UE for DL-OTDA (Downlink OTDOA) positioning. This Release 9 also requires the eNB(s) to be synchronized. It therefore removes the final obstacle for the OTDOA method (see paragraph 274 above). PRS improves UE audibility at multiple eNB UEs. Note that Release 9 did not specify eNB synchronization accuracy (100ns in some proposals).

U-TDOA/UL-TDOA is in the research stage and will be standardized in 2011.

The DL-OTDOA method (in Release 9) is detailed in US Pat. Release 9 DL-OTDOA suffers from multipath. Some of the multipath mitigation can be achieved by increasing the PRS signal bandwidth. However, the tradeoff is increased scheduling complexity and longer time between UE position fixes. Moreover, for a network with a limited operating bandwidth, say 10 MHz, the best possible accuracy is 100 meters, see Chen, Table 1.

The numbers above are the best possible case. In other cases, especially when the DLOS signal strength is significantly lower (10-20 dB) compared to the reflected signal(s) strength, it results in significantly larger (2x-4x) localization/ranging errors as described above. bring as

Embodiments described herein are adapted from Chen et al. allows up to a 50-fold improvement in ranging/location accuracy for a given signal bandwidth over the performance achieved by the Release 9 DL-OTDOA and UL-PRS methods of . Therefore, applying the method embodiments described herein to Release 9 PRS processing reduces the localization error to 3 meters or better in 95% of all possible cases. . In addition, this increased accuracy reduces scheduling complexity and time between UE position fixes.

Further improvements for the OTDOA method are possible with the embodiments described herein. For example, the ranging for the serving cell can be determined from other serving cells' signals, thus improving audibility of neighboring cells and reducing scheduling complexity, including the time between UE position fixes.

Embodiments are also described in Chen et al. , the U-TDOA method and the accuracy of the UL-TDOA can be improved up to 50 hours. Applying embodiments to Chen's UL-TDOA variant reduces the localization error to 3 meters or better in 95% of all possible cases. Moreover, this increase in accuracy further reduces scheduling complexity and time between UE position fixes.

Again, using this embodiment, the accuracy of Chen's UL-TDOA method can be improved by up to 50-fold. Therefore, applying this embodiment to Chen's U-TDOA variant reduces the localization error to 3 meters or better in 95% of all possible cases. Moreover, this increase in accuracy further reduces scheduling complexity and time between UE position fixes.

The DL-TDOA and U-TDOA/UL-TDOA methods described above rely on unidirectional measurements (ranging). This embodiment and virtually all other ranging techniques require that the PRS and/or other signals used in the process of unidirectional ranging be frequency and phase coherent. OFDM based systems like LTE are frequency coherent. However, the UE unit and eNB(s) are not phase or time synchronized by a common source such as UTC for a few nanoseconds, eg there is a random phase adder.

To avoid phase coherence affecting ranging accuracy, multipath processor embodiments compute different phases between ranging signal(s), e.g., reference signal, individual components (subcarriers) do. This eliminates the random phase term adder.

Chen et al. As identified above in the discussion of Chen et al. results in significantly improved accuracy in indoor environments compared to the performance achieved by For example, Chen, et al. DL-OTDOA and/or U-TDOA/UL-TDOA are primarily for outdoor environments, indoors (buildings, premises, etc.), DL-OTDOA and U-TDOA technologies may not work well, according to There is Several reasons are noted (see Chen, #161-164), including distributed antenna systems (DAS) commonly used indoors, whereby each antenna does not have a unique ID. ]

The embodiments described below operate with wireless networks that utilize OFDM modulation and/or its derivatives and reference/pilot/and/or synchronization signals. Therefore, the embodiments described below operate with LTE networks, as well as other wireless systems including other types of modulation with or without reference/pilot/and/or synchronization signals. as well as other wireless networks.

The approaches described herein are also applicable to other wireless networks, including WiMax, WiFi, and whitespace. Other wireless networks that do not use reference/pilot and/or synchronization signals use the following types of alternative modulation embodiments as described in US Pat. 2) the ranging signal element is embedded in the transmitted/received signal frame(s); and 3) the ranging signal element is embedded with the data. obtain.

An embodiment of the multipath mitigation range estimation algorithm described herein (and also described in US Pat. Nos. 6,300,000 and 6,000,000) consists of multipath reflections plus the direct path of the signal (DLOS). It works by providing an estimate of the bounds on the set.

An LTE DAS system creates multiple copies of the same signal seen at different time offsets to the mobile receiver (UE). Delays are used to uniquely determine the geometry of the antenna and mobile receiver. The signal seen by the receiver resembles that seen by a multipath environment, except for the main "multipath" component resulting from the sum of the offset signals from multiple DAS antennas.

The signal ensemble seen by the receiver is identical to the kind of signal ensemble embodiment designed to utilize, except that in this case the dominant multipath component is not the traditional multipath. The present multipath mitigation processor (algorithm) can determine the attenuation and propagation delay of DLOS and each path, eg reflections (see Equations 1-3 and related discussion). Multipath may be present due to the dispersive RF channel (environment), but the dominant multipath component in this signal set is associated with transmissions from multiple antennas. Embodiments of the present multipath algorithm can estimate these multipath components, isolate the range of the DAS antenna to the receiver, and provide the range data to a location processor (implemented in software). Depending on the geometry of the antenna placement, this solution can provide both X,Y and X,Y,Z location coordinates.

As a result, this embodiment does not require the addition of hardware and/or new network signal(s). Moreover, positioning accuracy can be dramatically reduced by 1) mitigating multipath, and 2) in the case of active DAS, the lower bound on positioning error can be dramatically reduced, e.g., from about 50 meters to about 3 meters. can be significantly improved, such as by

It is assumed that the position (location) of each antenna in the DAS is known. The signal propagation delay for each antenna (or with respect to other antennas) must also be determined (known).

For active DAS systems, signal propagation delays can be automatically determined using folding techniques whereby a known signal is sent round-trip and the round-trip time is measured. This folding technique also eliminates signal propagation delay variations (drift) due to temperature, aging, and the like.

Using multiple macrocells and associated antennas, picocells and microcells further enhance resolution by providing additional reference points. The above-described embodiments of individual range estimation in multiple replica signal ensembles from multiple antennas can be further enhanced by modifications to the signal transmission structure in the following two ways. The first is to time multiplex the transmissions from each antenna. A second approach is to frequency multiplex each of the antennas. Using both enhancements, time and frequency multiplexing simultaneously further improve the ranging and localization accuracy of the system. Another approach is to add a propagation delay to each antenna. The delay value is chosen to be long enough to exceed the delay spread in the particular DAS environment (channel), but so that the multipath caused by the additional delay does not result in ISI (inter-symbol interference). Less than the cyclic prefix (CP) length.

The addition of a unique ID or unique identifier for each antenna increases the efficiency of the resulting solution. For example, it eliminates the need for the processor to estimate all of the range from the signal from each of the antennas.

In one embodiment utilizing an LTE downlink, one or more reference signal(s) subcarriers, including pilot and/or synchronization signal(s) subcarriers, are used to determine subcarrier phase and amplitude. and its carrier phase and amplitude are then subjected to multipath interference mitigation and localization estimation using range-based location observables and multilateration and location consistency algorithms to edit out irrelevant points. It applies to multipath processors because of the generation of

Another embodiment takes advantage of the fact that the LTE uplink signal also includes a base to mobile device, reference signal, which also includes reference subcarriers. In fact, from the sweeping probing mode used by the network to allocate frequency bands to uplink devices, to the mode in which reference subcarriers are used to generate channel impulse responses and aid in demodulation of uplink signals, etc. There are two or more modes that contain these subcarriers up to . Also, similar to the DL PRS added in Release 9, additional UL reference signals may be added in upcoming and future standard releases. In this embodiment, the uplink signal is processed by multiple base units (eNBs) using the same range to phase, multipath mitigation processing to generate range-related observables. In this embodiment, a location integrity algorithm is used as established by the multilateration algorithm to compile irrelevant observable points to generate a localization estimate.

Yet another embodiment, one or more relevant reference subcarriers (including pilot and/or synchronization) for both LTE downlink and LTE uplink are collected, range for phase mapping is applied, multipath mitigation is Applied and bounded observables are estimated. These data are then combined in such a way as to provide a more robust set of observables about the location using multilateration and location consistency algorithms. The advantage is redundancy resulting in improved accuracy due to two different frequency bands for downlink and uplink, or in the case of TDD (Time Division Duplexing) which improves system coherence.

In a DAS (Distributed Antenna System) environment, where multiple antennas carry the same downlink signal from a micro-cell, the location consistency algorithm(s) may be applied to the reference signal(s) (including pilot and/or synchronization) sub- It is extended to separate the range of the DAS antenna from the observables generated by multipath mitigation processing from the carrier, as well as to obtain location estimates from multiple DAS emitter (antenna) ranges.

In a DAS system (environment), obtaining an accurate location estimate is only possible if the signal paths from individual antennas can be resolved with high accuracy, whereby the path error is reduced to the distance between the antennas. of only a fraction (10 meters or better accuracy). Since all existing techniques/methods cannot provide such accuracy in severe multipath environments (signals from multiple DAS antennas appear as induced severe multipath), existing techniques/methods cannot take advantage of the location consistency algorithm(s) and the above-described extensions of this localization method/technique in a DAS environment.

InvisiTrack multipath mitigation method and system for object identification and location finding, described in US Pat. , uplink, and/or both (downlink and uplink), and using multilateration and location alignment to generate location estimates. Use to generate range-based location observables.

In all of the above embodiments, a trilateration positioning algorithm may also be utilized.

DL-OTDOA location was specified in the LTE Release 9, Evolved Universal Terrestrial Radio Access (E-UTRA), Physical Channels and Modulations, 3GPP TS36.211 Release 9 technical specifications. However, it is not implemented by wireless operators (carriers). Downlink location, on the other hand, may be achieved within the current, eg, unmodified, LTE network environment by using existing physical layer measurement operation(s).

In LTE, UEs and eNBs are required to perform physical layer measurements of radio communication characteristics. Measurement definitions are specified in 3GPP TS36.214. These measurements are taken periodically and reported to higher layers for a variety of purposes, including intra- and inter-frequency handovers, inter-radio access technology (inter-RAT) handovers, timing measurements, as well as RRM ( used for other purposes in support of radio resource management).

For example, RSRP (reference signal received power) is the average power of all resource elements carrying a cell-specific reference signal over the entire bandwidth.

Another example is the RSRQ (Reference Signal Received Quality) measurement that provides additional information (RSRQ combines interference level as well as signal strength).

The LTE network provides the UE with an eNB neighbor list (for the serving eNB). Based on network knowledge configuration, the (serving) eNode B provides the UE with the identities of neighboring eNBs, etc. The UE then measures the signal quality of the neighbors it can receive. The UE reports results back to the eNodeB. Note that the UE also measures the signal quality of the serving eNB.

According to the specification, RSRP is defined as the linear average over the power contribution (in [W]) of the resource elements carrying the cell-specific reference signal within the considered measurement frequency bandwidth. The measurement bandwidth used by the UE to determine RSRP is subject to the UE implementation with restrictions that corresponding measurement accuracy requirements need to be met.

Considering the measurement bandwidth accuracy requirements, this bandwidth is quite large and the cell-specific reference signals used in RSRP measurements can be further processed to determine these reference signal subcarrier phases and amplitudes, The phase and amplitude are then applied to a multipath processor for multipath interference mitigation and range-based location observable generation. Additionally, other reference signals used in RSRP measurements, such as SSS (Secondary Synchronization Signal) may also be used.

Then, based on range observables from three or more cells, a location fix can be estimated using multilateration and location consistency algorithms.

As mentioned earlier, there are several causes of RF fingerprinting database instability, but one of the main causes is multipath (RF signatures are very sensitive to multipath). ). As a result, the localization accuracy of the RF fingerprinting method(s)/technique exhibits less than 100% variability depending on vertical uncertainty, i.e. device Z-height and/or antenna orientation. multipath dynamics, i.e. changes over time, environment (eg weather), human and/or object motion (see Non-Patent Document 6).

This embodiment can significantly improve the localization accuracy of RF fingerprinting because of the ability to find and characterize individual paths (multipath processors), including significantly attenuated DLOS. As a result, RF fingerprinting decisions for location determination can be supplemented with real-time multipath distribution information.

As mentioned above, location determination requires location-based synchronization in time. In wireless networks, these location references may include access points, macro/mini/pico and femto cells, as well as so-called small cells (eNBs). However, wireless operators do not enforce the synchronization accuracy required for accurate position determination. For example, in the case of LTE, the standard does not require time synchronization between eNB(s) for FDD (Frequency Division Duplexing) networks. For LTE TDD (Time Division Duplexing), this time synchronization accuracy is in the limit of +/- 1.5 microseconds. This equates to a location uncertainty of over 400 meters. Although not required, LTE FDD networks are also synchronized, but use longer limits (than 1.5 microseconds).

Wireless LTE operators are using GPS/GNSS signals to synchronize eNB(s) in frequency and time. LTE eNB needs to maintain a very precise carrier frequency, i.e. 0.05ppm for macro/minicells and slightly less accurate (0.1-0.25ppm) for other types of cells. Note that there is GPS/GNSS signals may also be able to achieve better than 10 nanoseconds of required time synchronization accuracy (for position location). However, network operators and network equipment manufacturers do not allow packet transport/internet/Ethernet networking by utilizing, for example, NTP (Network Time Protocol) and/or PTP (Precision Time Protocol), such as IEEE 1588v2PTP. We try to reduce the costs associated with GPS/GNSS units in favor of time synchronization.

IP network-based synchronization has the potential to meet the minimum frequency and time requirements, but lacks the GPS/GNSS accuracy required for position determination.

The approach described herein is based on GPS/GNSS signals and signals generated by eNBs and/or APs or other wireless network equipment. It may also be based on IP networking synchronization signals and protocols and signals generated by eNBs and/or APs or other wireless network equipment. This approach is also applicable to other wireless networks, including WiMax, WiFi, and whitespace.

The eNB signal is received by a Time Observation Unit (TMO) installed in the operator's eNB equipment (Fig. 12). The TMO also includes an external sync source input.

The eNB signal is processed by the TMO and time-stamped using a clock that is synchronized with the external sync source input.

External synchronization sources can be from GPS/GNSS and/or Internet/Ethernet networking, such as PTP or NTP.

A time-stamped processed signal, e.g. LTE start of frame (which could be other signals, especially in other networks), is also sent to the central TMO server (Internet/Ethernet) which generates, maintains and updates the database of all eNBs. It also contains the eNB (cell) location and/or cell ID, which is transmitted via the ® backhaul.

The UE and/or eNB(s) involved in the process of ranging and obtaining location fix subscribe to the TMO server, which returns the time synchronization offsets between the eNB(s) involved. These time synchronization offsets are used by UE and/or eNB(s) involved in the process of obtaining location fix and coordinating location fix.

Instead, location determination calculations and adjustments are performed by the TMO server when the UE and/or eNB(s) involved in the ranging process also provide the obtained ranging information to the TMO server. good too. The TMO server then returns an accurate (coordinated) position (location fix) determination.

If more than one cell eNB equipment is co-located, a single TMO can process and timestamp the signals from all eNB(s).

RTT (Round Time Trip) measurements (ranging) can be used for localization. The drawback is that RTT ranging is subject to multipath, which dramatically affects location accuracy.

RTT localization, on the other hand, generally does not require location-based synchronization (in time) and, in the case of LTE specifically, the eNB.

At the same time, when operating with wireless network pilot references and/or other signals, the multipath mitigation processor, method(s)/techniques, and algorithms described in US Pat. ), eg, identifying the multipath channel through which the RTT signal(s) is traversing. This allows correction of the RTT measurement as the actual DLOS time is determined.

With a known DLOS time, it is possible to obtain a location fix using trilateration and/or similar localization methods without the need for location reference synchronization in the eNB or time.

Despite the TMO and TMO servers in place, technology integration of invisibility tracking requires macro/mini/pico and small cell and/or UE (mobile phone) changes. These changes are limited only to SW/FW (software/firmware), which requires a lot of effort to retrofit the existing infrastructure. Also, in some cases, network operators and/or UE/mobile phone manufacturers/suppliers oppose equipment modifications. Note that a UE is a radio network user equipment.

This SW/FW change can be completely avoided if the TMO and TMO Server functions are extended to support invisibility tracking location techniques. In other words, another embodiment described below operates using wireless network signals, but does not require modification of wireless network equipment/infrastructure. Therefore, the embodiments described below work with LTE networks, and it is also applicable to other wireless systems/networks, including Wi-Fi.

Essentially, this embodiment creates a parallel wireless location infrastructure that uses wireless network signals to obtain location determination.

Similar to the TMO and TMO server, the invisibility tracking location infrastructure includes one or more Wireless Network Signal Acquisition Units (NSAUs) and collects and analyzes data from the NSAU(s) to determine range and and one or more Location Server Units (LSUs) that determine the location and convert it to eg a table of phone/UE IDs and locations on the fly. The LSU interfaces to the wireless network via the network's API.

A plurality of these units may be deployed at various locations within a large infrastructure. If the NSAU(s) have coherent timing, results for all that give better accuracy can be used.

Coherent timing can be obtained from a GPS clock and/or other stable clock sources.

NSAUs communicate with LSUs via LANs (Local Area Networks), Metro Area Networks (MANs), and/or the Internet.

In some installations/instances, the NSAU and LSU may be combined/integrated into a single unit.

To support location services using LTE or other wireless networks, transmitters are required to be clock and event synchronized within tight tolerances. Typically, this is accomplished by locking onto the GPS 1PPS signal. This results in timing synchronization in the local area to within 3 ns 1 sigma.

However, there are many instances where this kind of synchronization is impractical. This embodiment provides time offset estimation and tracking of time offsets between downlink transmitters in order to provide delay compensation values to the location process, thus as if the transmitters were clock and event synchronized. The location process can be treated as if . This is achieved by prior knowledge of the transmitting antenna (required for any location service) and the receiver with known a priori antenna locations. This receiver, called the synchronization unit, collects data from all of the downlink transmitters and their knowledge of a given location and calculates the offset timing from a preselected base antenna. These offsets are tracked by the system through the use of a tracking algorithm that compensates the downlink transmitter for clock drift. Note that the process of deriving pseudoranges from received data utilizes an invisibility tracking multipath mitigation algorithm (described in US Pat. Synchronization is therefore unaffected by multipath.

These offset data are used by the location processor (location server, LSU) to properly align the data from each downlink transmitter so that it is being generated by synchronized transmitters. looks like. Time accuracy is compatible with best 1-PPS tracking and supports 3 meter location accuracy (1 sigma).

The synchronous receiver and/or receiver antennas are positioned based on the optimum GDOP for best performance. In large installations, multiple synchronization receivers can be utilized to provide equivalent 3ns1 sigma synchronization offsets throughout the network. By utilizing the synchronization receiver(s), the requirement for downlink transmitter synchronization is eliminated.

A synchronous receiver unit may be a stand-alone unit that communicates with the NSAU and/or LSU. Alternatively, this synchronization receiver may be integrated with the NSAU.

An exemplary wireless network locating equipment diagram is depicted in FIG.

An embodiment of a fully autonomous, non-customer network investment, system utilizing LTE signals operates in the following modes.
1. Uplink mode uses wireless network uplink (UL) signals for location purposes (FIGS. 16 and 17).
2. Downlink mode uses wireless network downlink (DL) signals for location purposes (FIGS. 14 and 15).
3. Bi-directional mode—uses both UL and DL signals for location.
In uplink mode, multiple antennas are connected to one or more NSAUs. These antenna locations are independent of the radio network antenna, and the NSAU(s) antenna locations are chosen to minimize GDOP (Geometric Loss of Accuracy).

Network RF signals from UE/cellular devices are collected by the NSAU(s) antenna(s), processed by the NSAU(s) and suitable for capturing one or more instances of all signals of interest. produces time-stamped samples of the network RF signal processed during the time interval.

Optionally, the NSAU also receives process and time-stamped samples of the downlink signal to obtain additional information, such as to determine UE/phone ID.

From the captured time-stamped samples, along with time-stamped wireless network signals of interest associated with each UE/mobile phone ID(s), a UE/mobile phone device identification number (ID) is determined. ) is done. This operation can be performed by either the NSAU or the LSU.

The NSAU periodically supplies data to the LSU. If unscheduled data is required for one or more UE/mobile ID(s), the LSU requests additional data.

No changes/modifications are required in the radio network infrastructure and/or existing UEs/mobile phones for UL mode operation.

Downlink (DL) mode requires a UE capable of invisibility tracking. Also, the mobile phone FW needs to be modified if the phone is used to obtain location determination.

In some instances, an operator may make baseband signals available from BBU(s) (baseband units). In such cases, the NSAU(s) may also process these available baseband wireless network signals instead of RF wireless network signals.

In DL mode, there is no need to associate a UE/mobile ID with one or more radio network signals. because these signals are processed at the UE/mobile phone, or the UE/mobile phone periodically generates time-stamped samples of the processed network RF signals and transmits them to the LSU, This is because the LSU will send the result(s) back to the UE/mobile phone.

In DL mode, the NSAU processes and timestamps processed RF or baseband (if available) wireless network signals. From the captured time-stamped samples, the wireless network signal DL frame starts associated with the network antennas are determined (obtained) and the difference (offset) between these frame starts is calculated. This operation can be performed by either the NSAU or the LSU. Frame start offsets for network antennas are stored on the LSU.

In DL mode, the frame start offset of the network antenna is transmitted from the LSU to the UE/telephone device when the device uses invisibility tracking techniques to process/determine its own location determination. Instead, when the UE/cellular device periodically transmits time-stamped samples of the processed network RF signal to the LSU, the LSU determines device location determination and sends location determination data to the device. Send back to

In DL mode, wireless network RF signals come from one or more wireless network antennas. To avoid multipath affecting the accuracy of results, the RF signal must be found from the antenna or antenna connection to the wireless network equipment.

Bi-directional mode encompasses location determination from both UL and DL operations. This allows for further improvements in localization accuracy.

Some enterprise setups are one or more BBUs feeding one or more Remote Radio Heads (RRHs), each RRH in turn feeding multiple antennas with the same ID. Use BBU. In such circumstances, depending on the wireless network configuration, determination of the network antenna DL mode frame start offset may not be required. This includes multiple BBUs as well as a single BBU setup, whereby each BBU's antennas are assigned to certain zones, and the coverage of adjacent zones overlaps.

On the other hand, configurations whereby antennas fed from multiple BBUs are interleaved within the same zone require determination of the DL mode frame start offset of the network antennas.

In a DL mode of operation in a DAS environment, multiple antennas may share the same ID.

In this embodiment, the location consistency algorithm(s) is the range of the DAS antenna from the observables generated by multipath mitigation processing from the reference signal(s) subcarriers (including pilot and/or synchronization). , and to obtain location estimates from multiple DAS emitter (antenna) coverage.

However, these matching algorithms are limited in the number of antennas emitting the same ID. The number of antennas emitting the same ID can be reduced by:
1. For a given coverage zone interleaving, antennas fed from different sectors of a sectorized BBU (BBU can support up to 6 sectors)
2. For a given coverage zone interleaving, antennas fed from different sectors of a sectorized BBU and antennas fed from different BBUs3. Add a propagation delay element to each antenna. The delay value is large enough to exceed the delay spread in a particular DAS environment (channel), but the multipath caused by the additional delay does not result in ISI (inter-symbol interference). (CP) is chosen to be less than the length. Adding a unique delay ID for more than one antenna further reduces the number of antennas emitting the same ID.

In some embodiments, an autonomous system with no customer network investment may be proposed. In such embodiments, the system may operate on bands other than the LTE band. For example, ISM (Industrial, Scientific and Medical) bands and/or whitespace bands may be used in locations where LTE service is not available.

Embodiments may also be integrated with macro/mini/pico/femto station(s) and/or UE (mobile phone) equipment. Although consolidation may require customer network investment, it can reduce overheads and dramatically improve TCO (total cost of ownership).

As described herein above, PRS may be used by a UE for downlink observed time difference of arrival (DL-OTDOA) positioning. For neighbor base station (eNB) synchronization, 3GPP TS36.305 (Stage 2 Functional Specification for User Equipment (UE) Positioning in E-UTRAN) specifies the transmission timing for the UE, which is a candidate It relates to eNodeB services in a cell (eg, neighboring cells). 3GPP TS36.305 also defines the physical cell ID (PCI) and global cell ID (GCI) of candidate cells for measurement purposes.

According to 3GPP TS36.305, this information is delivered from an E-MLC (Enhanced Serving Mobile Location Center) server. Note that TS36.305 does not specify the timing accuracy mentioned above.

Furthermore, 3GPP TS36.305 specifies that the UE shall return downlink measurements to the E-MLC, including reference signal time difference (RSTD) measurements.

RSTD is a measurement made between a pair of eNBs (see TS 36.214 Evolved Universal Terrestrial Radio Access (E-UTRA), Physical Layer Measurements, Release 9). A measurement is defined as the relative timing difference between the subframes received from neighbor cell j and the corresponding subframes of serving cell i. A positioning reference signal is used to make these measurements. Results are reported back to the location server, which computes the location.

In some embodiments, a hybrid method may be defined to accommodate both newly introduced PRS and existing reference signals. In other words, the hybrid method can be used/operated with PRS, with other reference signals (eg, cell or node specific reference signals (CRS)), or with both signal types.

Such a hybrid method offers the advantage of allowing the network operator(s) to dynamically select the mode of operation depending on the circumstances or network parameters. For example, PRS has better audibility than CRS, but can result in up to 7% reduction in data throughput. On the other hand, CRS signals do not result in any throughput reduction. In addition, CRS signaling is backwards compatible with all previous LTE releases, eg Release 8 and below. As such, the hybrid method provides network operators with the ability to trade off or balance between audibility, throughput, and compatibility.

In Long Term Evolution (LTE) implementations, LTE downlink baseband signals (generated by cells or radio nodes, referred to herein as "nodes") are typically combined into downlink frames. A receiver for detecting and receiving such signals may detect downlink frames from multiple (more than one) cells or nodes. Each downlink frame contains multiple CRSs or reference signals. In downlink (DL) frames, these reference signals have pre-determined positions in time and frequency, e.g., there is a deterministic time offset between the frame start and each CRS in a given frame. do.

Furthermore, each CRS is modulated with a special code. Modulation and code are also predetermined. The CRS modulation is the same for all nodes, but the code (seed) is determined by the node's ID (identification) number.

As a result, by knowing the node ID(s), it is possible to estimate where in the spectrum of the reference signal from each node (cell) the frame start time has elapsed for each frame. To do so, it is necessary to first determine the frame start time or frame start for all DL signals from different nodes. For example, in one embodiment, various A full CRS sequence or other reference signal can be found from a node, and this information can be used to find the coarse location frame start of all observable nodes. In some embodiments, the detector may also demodulate/decode the CRS and then correlate the demodulated/decoded CRS with the baseband subcarriers assigned to the CRS.

At the same time, in some embodiments, the CRS may also be used as a ranging signal by the multipath mitigation processor. Therefore, in addition to finding the coarse frame start, the detector correlation process also extracts from other signals in the frame (such as the payload) using the code used to modulate those signals. , CRS can be separated. These separated CRSs and associated frame starts are then forwarded to the multipath mitigation processor for ranging.

A similar approach can be used in uplink mode, whereby timing offsets between different node receivers can be determined.

In a downlink embodiment, a system for tracking and locating one or more wireless network devices communicating with a network is configured to receive a plurality of signals from two or more nodes communicating with the network. an equipment receiver, wherein a plurality of signals are modulated with a code determined by an identity of each node of two or more nodes transmitting the plurality of signals, and a user equipment receiver selects a plurality of nodes based on the identities; and a reference signal as a ranging signal from each node for tracking and locating one or more wireless network devices a processor configured to use

In an embodiment, multiple signals from each node of the two or more nodes are combined into a frame containing the reference signal, and the detector is further configured to estimate the elapsed location of the frame start from each node.

In embodiments, the detector is further configured to estimate the travel location by correlating the reference signal with known replicas of such reference signal.

In embodiments, the detector is further configured to separate the reference signal from any other signal in the frame, and the detector is further configured to separate the reference signal for each node of the two or more nodes. be done.

In an embodiment, the processor is at least one multipath mitigation processor, which receives the travel locations and the separated reference signals to estimate the relative time of arrival of the ranging signal from each node. configured as

In embodiments, the processor is at least one multipath mitigation processor.

In an embodiment, the multiple signals from each node of the two or more nodes are within a frame, the detector is further configured to estimate the elapsed location of the frame start from each node, and the detector is , configured to separate the reference signal from any other signal in the frame, a detector further configured to separate the reference signal for each node of the two or more nodes, the detector for each node to a multipath mitigation processor, the multipath mitigation processor receiving the elapsed locations and the isolated reference signals to determine the relative ranging signal from each node Configured to estimate time of arrival.

In embodiments, the system further comprises an uplink embodiment in which the node receiver is configured to receive device signals from one or more wireless network devices, the device signals transmitting device signals from one or more A device modulated with a device code determined by the device identification of each wireless network device of the wireless network devices, the node receiver configured to detect and separate the device reference signal from the device signal based on the device identification. A second processor, including a detector, is configured to use the device reference signal from each wireless network device as a ranging signal to track and locate the one or more wireless network devices.

In one embodiment, a system for tracking and locating one or more wireless network devices in communication with a network is user equipment configured to receive a plurality of signals from two or more nodes in communication with the network. a receiver, a user equipment receiver in which the plurality of signals are modulated with a code determined by the identity of each of the two or more nodes transmitting the plurality of signals; a processor configured to detect and isolate the reference signal from the signals of and to use the reference signal as a ranging signal from each node to track and locate one or more wireless network devices; Prepare.

In an embodiment, multiple signals from each node of the two or more nodes are combined into a frame containing the reference signal, and the processor is further configured to estimate from each node the elapsed location of the frame start.

In an embodiment, the processor is further configured to estimate the travel location by correlating the reference signal with known replicas of the reference signal.

In embodiments, the processor is further configured to estimate the relative time of arrival of the ranging signal from each node based on the location of travel and the isolated reference signal.

In embodiments, the processor is further configured to separate the reference signal from any other signals in the frame, and the processor is further configured to separate the reference signal for each node of the two or more nodes. .

In an embodiment, multiple signals from each node of the two or more nodes are within a frame, and the processor determines the start of frame from each node by correlating the reference signal with known replicas of the reference signal. Further configured to estimate the elapsed location, the processor further configured to separate the reference signal from any other signals in the frame, and to separate the reference signal for each node of the two or more nodes. and the processor is further configured to estimate the relative time of arrival of the ranging signal from each node based on the location of travel and the isolated reference signal.

In one embodiment, a system for tracking and locating one or more wireless network devices in communication with a network has a detector configured to receive a plurality of signals from two or more nodes in communication with the network. wherein the plurality of signals are modulated with a code determined by the identity of each node of the two or more nodes carrying the plurality of signals, and detecting and separating the reference signal from the plurality of signals based on the identity and a processor configured to use the reference signal as a ranging signal from each node to track and locate one or more wireless network devices.

In an embodiment, multiple signals from each node of the two or more nodes are combined into a frame containing the reference signal, and the detector is further configured to estimate the elapsed location of the frame start from each node.

In embodiments, the detector is further configured to estimate the travel location by correlating the reference signal with known replicas of such reference signal.

In embodiments, the detector is further configured to separate the reference signal from any other signal in the frame, and the detector is further configured to separate the reference signal for each node of the two or more nodes. be done.

In an embodiment, the processor is at least one multipath mitigation processor, which receives the travel locations and the separated reference signals to estimate the relative time of arrival of the ranging signal from each node. configured as

In embodiments, the processor is at least one multipath mitigation processor.

In an embodiment, the multiple signals from each node of the two or more nodes are within a frame, the detector is further configured to estimate the elapsed location of the frame start from each node, and the detector is , configured to separate the reference signal from any other signal in the frame, a detector further configured to separate the reference signal for each node of the two or more nodes, the detector for each node to a multipath mitigation processor, the multipath mitigation processor receiving the elapsed locations and the isolated reference signals to determine the relative ranging signal from each node Configured to estimate time of arrival.

In one embodiment, a system for tracking and locating one or more wireless devices communicating with a network is a node receiver configured to receive device signals from one or more wireless network devices, , the device signal is modulated with a device code determined by the device identification of each of the one or more wireless network devices transmitting the device signal, and a node receiver modulates the device signal from the device signal based on the device identification; A node receiver including a device detector configured to detect and isolate device reference signals and devices as ranging signals from each wireless network device to track and locate one or more wireless network devices. a processor configured to use the reference signal.

Furthermore, the hybrid method may be transparent to the LTE UE positioning architecture. For example, the hybrid method can operate in the 3GPP TS36.305 framework.

In an embodiment, RSTD may be measured and transferred from the UE to the E-SMLC according to 3GPP TS36.305.

UL-TDOA (U-TDOA) is currently in the research stage and is expected to be standardized in the upcoming Release 11.

UL-TDOA (Uplink) embodiments are described herein above and shown in FIGS. Figures 18 and 19, described herein below, provide alternative example embodiments of UL-TDOA.

FIG. 18 represents an environment that may include one or more DAS and/or femto/small cell antennas. In this example embodiment, each NSAU is equipped with a single antenna. As depicted, at least three NSAUs are required. However, since each UE needs to be "heard" by at least three NSAUs, additional NSAUs can be added to improve audibility.

Furthermore, the NSAU(s) may be configured as a receiver. For example, each NSAU receives information over the air, but does not transmit that information. In operation, each NSAU can listen to radio uplink network signals from UEs. Each of the UEs may be a mobile phone, tag, and/or another UE device.

Additionally, the NSAU may be configured to communicate with a Location Server Unit (LSU) over an interface, such as a wireline service or LAN. The LSU can then communicate with a wireless or LTE network. Communication may be via a network API, where the LSU may, for example, communicate with an E-SMLC in an LTE network and may use wireline services such as LAN and/or WAN.

Optionally, the LSU may also communicate directly with the DAS base station(s) and/or femto/small cells. This communication may use the same or modified network APIs.

In this embodiment, Sounding Reference Signals (SRS) may be used for location purposes. However, other signals may also be used.

The NSAU can convert the UE uplink transmission signal into digital form, eg, I/Q samples, and periodically send some converted signals with timestamps to the LSU.

The DAS base station(s) and/or femto/small cells can pass one or all of the following data to the LSU.
1) SRS, I/Q samples and timestamps;
2) a list of provided UE IDs; and 3) an SRS schedule for each UE with the UE ID, including SRS scheduling request Config information and SRS-UL-Config information.

The information passed to the LSU may not be limited by the above information. It may contain any information necessary to correlate each UE device uplink signal, eg, UE SRS, with each UE's ID.

LSU functions may include ranging calculations and obtaining location determination for the UE. These decisions/calculations may be based on information passed to the LSU from the NSAU, DAS base stations, and/or femto/small cells.

The LSU may also determine the timing offset from available downlink transmission information passed to the LSU from the NSAU.

The LSU can then provide UE location determination and other calculations and data to the wireless or LTE network. Such information may be communicated via network APIs.

For synchronization purposes, each NSAU may receive, process, and timestamp samples of the downlink signal. Each NSAU may also periodically send a number of such samples, including timestamp(s), to the LSU.

Additionally, each NSAU may include an input configured for synchronization with external signal(s).

FIG. 19 depicts another embodiment of UL-TDOA. In addition to the components depicted under FIG. 18, the environment of this embodiment may include one or more cell towers that may be used in place of DAS base stations and/or femto/small cells. Data from one or more cell towers may be used to obtain location determination for the UE.

As such, advantages of this embodiment include obtaining location determination using only a single cell tower (eNB). Additionally, this embodiment is configured to operate in a manner similar to that described under FIG. 18, except that one or more eNBs can replace DAS base stations and/or femto/small cells can be

One method of UE uplink location is the Cell Identification Method (CID). In the basic CID method, UE location can be determined at the cell level. This method is purely network-based. As a result, the UE, eg the handset, is unaware of the fact that it is being tracked. Although this is a relatively simple method, it lacks accuracy because the localization uncertainty is equal to the cell diameter. For example, as illustrated in FIG. 20, any of the handsets 2000 within cell diameter 2002 of serving cell tower 2004 have substantially the same location even though they are not co-located. The accuracy of the CID method can be improved when combined with serving sector identification (sector ID) knowledge. For example, as illustrated in FIG. 21, sector ID 2100 is within cell diameter 2002 containing some handsets 2104 known to have different locations than other handsets 2000 in other sectors of cell diameter 2002 . identifies the section 2102 of the .

Further enhancements to the CID method may be possible through the Enhanced Cell-ID (E-CID) method, which provides further improvements to the basic CID method described above. One enhancement uses timing measurements to calculate how far the UE is from the eNB (network node). This distance can be calculated as half the round trip time (RTT), or the timing advance (TA) in LTE (LTE TA) multiplied by the speed of light. When the UE is connected, RTT or TA may be used for range estimation. In this case, both the serving cell tower or sector and the UE (immediately after the serving eNB command) measure the timing difference between the Rx and Tx subframes. The UE reports its measurements to the eNB (and under eNB control). Note that LTE Release 9 adds a TA type 2 measurement that relies on the timing advance estimated from receiving the PRACH preamble during the random access procedure. The PRACH (Physical/Packet Random Access Channel) preamble defines the maximum number of preambles that are sent during one PRACH ramping cycle when no response is received from the tracked UE. An LTE type 1TA measurement is equivalent to an RTT measurement as follows.
RTT = TA (type 1) = eNB (Rx - Tx) + UE (Rx - Tx)
With knowledge of the eNB's coordinates and the height of the serving cell tower antenna, the UE's location can be calculated by the network.

However, since in one dimension the location accuracy depends on the sector width and distance from the serving cell tower, and in the other dimension the error depends on the TA (RTT) measurement accuracy, the E-CID location method is still limited. Sector width varies with network topology and is affected by propagation phenomena, specifically multipath. Sector accuracy estimates vary from 200 meters to over 500 meters. The LTE TA measurement resolution is 4Ts, which corresponds to a maximum error of 39 meters. However, the actual error in LTE TA measurements is much larger due to calibration inaccuracies and propagation phenomena (multipath) and can reach as much as 200 meters.

As illustrated in FIG. 22, the E-CID method can be further improved with the addition of a feature known as the Angle of Arrival (AoA). The ENB estimates the direction from which the UE is transmitting using a linear array of evenly spaced antenna elements 2200 . Typically, a reference signal is used for AoA determination. When a reference signal is received from a UE at two adjacent antenna elements 2200, the reference signal may be phase rotated by an amount that depends on the AoA, carrier frequency, and element spacing, as shown in FIG. AoA requires each eNB to be equipped with an antenna array/adaptive antenna. It is also subject to multipath and topology variations. Nevertheless, sophisticated antenna arrays can significantly reduce the width 2202 of sector 2100, which can lead to good location accuracy. Moreover, as illustrated in FIG. 23, if two or more serving cell towers 2300 (eNB base stations equipped with directional antenna arrays) can be used to make handset AoA decisions, the accuracy can be greatly improved. In such cases, accuracy is still subject to multipath/propagation phenomena.

Deploying antenna arrays/adaptive antennas over multiple LTE bands across a network requires a tremendous effort in terms of capital, time, maintenance, and so on. As a result, antenna arrays/adaptive antennas are not deployed for UE localization purposes. Other approaches, such as those based on signal strength, do not provide significant accuracy improvements. One such signal strength approach is fingerprinting, which requires a large, continuously changing (in time) fingerprinting database, e.g. Requires reincurrence of spending without improvement of Moreover, fingerprinting is a UE-based technique, whereby the UE location cannot be determined without UE assistance at the UE application level.

Solutions to the limitations of other uplink localization methods include using AoA functionality without the need for antenna arrays/adaptive antennas. Such embodiments may utilize a TDOA (time difference of arrival) localization technique for AoA determination, which may be based on estimates of differences in arrival times of signals from sources at multiple receivers. Each value of the time difference estimate defines a hyperbola between two receivers communicating with the UE. When the distance between the receiving antennas is small relative to the distance at which the emitter (handset) is located, TDOA is equal to the angle between the baseline of the sensor (receiver's antenna) and the incident RF energy from the emitter. If the angle between the baseline and true north is known, the line of bearing (LOB) and/or AoA can be determined.

Although common localization methods using either TDOA or LOB (also known as AoA) are known, the TDOA reference points are too close together to make the accuracy of such techniques acceptable. , the TDOA location method has not been used to determine LOBs. Rather, LOBs are typically determined using directional and/or beamforming antennas. However, the super-resolution method described herein allows dramatically improved accuracy while using TDOA for LOB determination. Furthermore, without the reference signal processing techniques described herein, it would be impossible to "listen", e.g., detect, reference signals coming from UEs outside the serving sector, e.g., by non-serving sectors and/or antennas. may not be possible. Utilizing TDOA for LOB determination, because without the resolution and processing capabilities described herein, at least two reference points (e.g., two or more sectors and/or antennas) are required may not be possible. Similarly, the UE may not be able to detect reference signals coming to the UE from non-serving sectors, eg, non-serving sectors and/or antennas.

For example, FIG. 24 illustrates two antenna separation scenarios: wide open separation and close (small) separation. In both scenarios, the hyperbola 2400 and the line of incidence 2402 intersect at the location of the handset 2000, but this occurs at a steeper angle when the antenna 2404 separation is wide open, which then Substantially reduce localization errors. At the same time, hyperbola 2400 becomes interchangeable with incident line of RF energy 2402 or LOB/AoA when antennas 2404 are close to each other.

によって与えられ、
ここで、
Δｔは、秒単位の、時間差であり、
ｘは、メートル単位の、２つのセンサ間の距離であり、
Θは、度単位の、センサの基線及び入射ＲＦ波間の角度であり、
ｃは、光速である。 The formula defined below can be used to determine the incident RF energy from the emitter, where the time difference in the arrival times of the RF energy between the two antennas (sensors) is:

given by
here,
Δt is the time difference, in seconds;
x is the distance between the two sensors in meters;
Θ is the angle in degrees between the sensor baseline and the incident RF wave;
c is the speed of light.

Some localization techniques are: (1) TDOA measurements between two or more serving cells (multi-lateration) are available, e.g., when there is a wide open separation; (3) a combination of techniques (2) and (3), and (4) TA measurements and techniques when only from two or more sectors in the serving cell above, e.g., small antenna separation, such LOB/AoA only Combinations of (1)-(3) are available through the use of TDOA localization embodiments, including, for example, improved E-CID.

As explained further below, in the case of closely positioned antennas, the TDOA locating embodiment uses bearing lines when the signals from two or more antennas are from the same cell tower. obtain. These signals can be detected in the received composite signal. By knowing the location and azimuth angle of each sector and/or antenna tower, a azimuth line and/or AoA can be calculated and utilized in the location process. LOB/AoA accuracy can be affected by multipath, noise (SNR), and so on. However, this effect can be mitigated by the advanced signal processing and multipath mitigation processing techniques described above, which can be based on super-resolution techniques. Such advanced signal processing includes, but is not limited to, signal correlation/correlation, filtering, averaging, synchronous averaging, and other methods/techniques.

Serving cell tower 2500 typically consists of multiple sectors, which show a three sector (Sector A, Sector B, and Sector C) configuration, as illustrated in FIG. The illustrated three sector deployment may include one or more antennas 2502 per sector. A single sector, eg, sector A, may be under the control of the UE (handset) because the handset transmission is within the main lobe of sector A (the center of the main lobe coincides with the sector azimuth). At the same time, handset transmissions belong outside the main lobes of sectors B and C, eg, in the side lobes of the antenna. Therefore, the handset signal is still present in the output signal spectrum of sectors B and C, but is significantly attenuated relative to signals from other handset(s) located in the main lobes of sector B or sector C. . Nonetheless, through the use of advanced signal processing, as described above and below, we obtain sufficient processing gain on the ranging signal to reduce them to neighboring sector sidelobes, e.g., sector B and sector C sidelobes. and so on. For network-based location purposes, LTE uplink SRS (Sounding Reference Signal) may be utilized as a ranging signal.

In other words, the UE uplink reference signal may be within the sidelobes of the neighboring sector(s) antenna, but the processing gain with the reference signal processing methods described herein is two (or more). may be sufficient to allow calculation of TDOA between sector antennas. The accuracy of this embodiment can be significantly enhanced by the multipath mitigation processing algorithm described above. Therefore, a LOB/AOA that intersects the annulus calculated by LTE TA timing may provide UE location to within an error ellipse of approximately 20 meters by 100 meters.

Further location error reduction can be achieved when the UE can be heard by more than one LTE tower, which most likely uses the processing gain and multipath mitigation techniques described above. In such a case, the intersection of the TDOA hyperbola and one or more LOB/AoA lines may result in an error ellipse of 30x20 meters (for two sector cell towers). If each cell tower supports more than two sectors, the error ellipse can be further reduced to 10-15 meters. Accuracy of 5-10 meters can be achieved if the UE is listened to by 3 or more eNB's (cell towers). In high value areas, such as malls, office parks, and similar locations, additional small cells or passive listening devices may be used to produce the necessary coverage.

As previously described, each such sector of cell tower 2500 may include one or more antennas 2502 . In a typical installation, for a given sector, the signals from each antenna are combined at the sector's receiver input. As a result, for location purposes, two or more sector antennas can be viewed as a single antenna with a compound directional pattern, azimuth, and elevation. The virtual antenna composite directivity as well as its (mainlobe) azimuth and altitude may also be assigned to the sector itself.

In one embodiment, received signals (in digital form) from all sectors of each serving cell tower and neighboring serving cell towers are sent to a Location Server Unit (LSU) for location determination. Also, the SRS schedule and TA measurements for each served UE are provided to the LSU by each serving sector from each serving cell tower. Assuming that the location coordinates of each serving cell tower and each neighboring cell tower field, the number of sectors per tower with each virtual (composite) sector antenna azimuth and altitude, and the location of each sector in the cell tower are known, the LSU is , the serving cell tower and/or the neighboring cell towers. All of the information described above may be transmitted over wired networks, such as LANs, WANs, etc., using one or more standardized or proprietary interfaces. The LSU may also interface with the wireless network infrastructure using standardized interfaces and/or network carrier defined interfaces/APIs. Location determination may also be distributed between network nodes and LSUs, or may be performed solely at network nodes.

In some embodiments, the location determination may be made at the UE or distributed between the UE and LSU or network nodes. In such cases, the UE may communicate wirelessly using standard networking protocols/interfaces. Additionally, location determination may be made through a combination of UE, LSU and/or network nodes, or the LSU function may reside within the SUPL Server, E-SMLC Server, and/or LCS (LoCation Service) system. can be implemented (embedded) and they can then be used instead of LSUs.

The downlink (DL) location method embodiments are contrary to the uplink (UL) location embodiments described above. In a DL embodiment, a sector may be a transmitter with a transmission pattern, azimuth and altitude matching the received directionality, azimuth and altitude of the sector. Unlike uplink embodiments, in DL embodiments the UE typically has a single receive antenna. Therefore, for the UE there is no sensor baseline that can be used to determine RF wave incidence. However, the UE can determine the TDOA(s) between different sectors and consequently the hyperbola(s) between sectors (multilateration), since sectors of the same cell tower are close to each other, hyperbolic becomes interchangeable with RF energy incident line or LOB/AoA as described above with respect to FIG. LOB/AoA accuracy can be affected by multipath, noise (SNR), etc., but this impact can be mitigated through the use of advanced signal processing and multipath mitigation processing based on the super-resolution techniques described above. .

As noted above, UE DL localization can be accomplished in a similar manner to UE uplink localization, except that the RF wave incidence angle cannot be determined from the above equation. Alternatively, multilateration techniques may be used to determine the LOB/AoA for each serving cell tower.

UE DL location embodiments also utilize reference signals. In the DL case, one approach for such network-based location may be to utilize LTE cell-specific reference signals (CRS) as ranging signals. Also, the Position Reference Signal (PRS) introduced in LTE Release 9 may be used. Therefore, location can be performed using CRS only, PRS only, or both CRS and PRS.

As in the UE uplink localization embodiment, for the UE downlink localization embodiment, a snapshot of the UE received signal in digital form may be sent to the LSU for processing. The UE may also obtain TA measurements and provide them to the LSU. Optionally, each supplied per-UE TA measurement may be provided to the LSU by each serving sector from each serving cell tower (network node). As previously described, the LSU may determine each UE's location relative to the serving cell tower and/or neighboring cell towers. In embodiments, the location determination may be made at the UE or distributed between the UE and LSU or network nodes. In embodiments, all location determination may be made at the LSU or network node, or distributed between the two.

The UE wirelessly communicates/receives measurements and other information using standard wireless protocols/interfaces. Information exchange between the LSU and network node(s) may be over a wired network, eg, LAN, WAN, etc., using proprietary and/or one or more standardized interfaces. The LSU may interface with the wireless network infrastructure using standardized interfaces and/or network carrier defined interfaces/APIs. Location determination may also be distributed between network nodes and LSUs, or may be performed solely at network nodes.

For the UE DL location embodiments described above, antenna port mapping information may also be used to determine location. The 3GPP TS36.211 LTE standard defines antenna ports for DL. A separate reference signal (pilot signal) is defined in the LTE standard for each antenna port. Therefore, the DL signal also carries antenna port information. This information is contained in the PDSCH (Physical Downlink Shared Channel). PDSCH uses the following antenna ports: 0, 0 and 1, 0, 1, 2, and 3), or 5. These logical antenna ports are assigned (mapped) to physical transmit antennas as illustrated in FIG. As a result, this antenna port information can be used for antenna identification (Antenna ID).

For example, antenna port mapping information can be used to determine RF wave incidence and hyperbola(s) (multilateration) between antennas (assuming antenna locations are known). Depending on where the location determination is made, antenna mapping information needs to be available to the LSU or UE or network node. Note that antenna ports are indicated by placing the CRS signals in different time slots and different resource elements. Only one CRS signal is transmitted per DL antenna port.

In the case of MIMO (multiple-input multiple-output) deployments at eNBs or network nodes, the receiver(s) may be able to determine the time difference of arrival from a given UE. With knowledge of the antenna to receiver(s) mapping, e.g., MIMO mapping, including antenna location, the RF wave incident on the antenna (LOB/AoA) and the hyperbola(s) for a given eNB antenna ( multilateration) can also be determined. Similarly, at the UE, the UE receiver(s) can determine the time difference(s) of arrival from two or more eNBs or network nodes and MIMO antennas. With knowledge of eNB antenna locations and antenna mapping, it is possible to determine the RF wave incidence (LOB/AoA) from the antennas and the hyperbola(s) (multilateration) for a given eNB antenna. . Depending on where the location determination is made, antenna mapping information needs to be available to the LSU or UE or network node.

Other configurations exist that are subsets of MIMO, eg, single-input multiple-output (SIMO), single-output multiple-input (SOMI), single-input single-output (SISO), and so on. All of these configurations may be defined/determined by antenna port mapping and/or MIMO antenna mapping information for location purposes.

In one aspect, the present embodiments relate to methods and systems for RF-based identification, tracking, and localization of objects, including RTLS. According to one embodiment, the method and system provide for geographically dispersed clusters of receivers and/or transmitters that are synchronized precisely in time, eg, within 10 ns or better, within each cluster. , but time synchronization between clusters may not be very accurate or required at all. Precise synchronization times of 10 ns or better are described for certain embodiments, but the predetermined synchronization time required to achieve accurate position determination will depend on the equipment being utilized. It is important to note that For example, for some wireless system equipment, if an accuracy of 3m is required for accurate location determination, the predetermined time may need to be 10ns or better, whereas other wireless systems For instruments, a 50m location accuracy may be more than sufficient. The predetermined time is therefore based on the desired location accuracy for the wireless system. The disclosed methods and systems are significant improvements over existing implementations of tracking and localization DL-OTDOA and U-TDOA techniques, which include geographically dispersed standalone (individual) transmitters and/or rely on the receiver.

For example, in the DL-OTDOA technique, the relative timing difference between signals coming from neighboring base stations (eNBs) is calculated and the UE position is determined either in networks with UEs (handsets) with or without UE assistance, or with network assistance. It can be estimated at the UE (handset) with (SUPL-based only control plane or user plane) or without network assistance. In DL-OTDOA, once signals from three or more base stations have been received, the UE measures the relative timing difference between the signals coming from a pair of base stations to create a hyperbolic line of position (LOP). produce. At least three reference points (base stations not belonging to a straight line) are required to define two hyperbolas. The UE location (position fix) is at the intersection of these two hyperbolas (see Figure 11). UE position fix is related to the (antenna) location of the base station's RF emitter. As an example, when using LPP (LTE Positioning Protocol, Release 9), DL-OTDOA location is UE assisted and E-SMLC (Evolved Serving Mobile Location Center) is server-based .

The U-TDOA technique is similar to DL-OTDOA, but the roles are reversed. Here, a neighborhood management unit (LMU) calculates the relative arrival times of uplink signals coming from a UE (handset) so that the UE's position can be estimated in the network without the UE's assistance. Hence, U-TDOA is LMU-assisted and E-SMLC (Evolved Serving Mobile Location Center) is server-based. Once relative time-of-arrival values from three or more LMUs are available, the network's E-SMLC server creates a hyperbolic line of position (LOP) and location (location fix) for the UE (see Figure 27). . UE position determination is related to the LMU antenna location. In an aspect, unlike DL-OTDOA, no eNB (base station) time synchronization is required in the U-TDOA case, and only the LMU(s) need high-precision time synchronization for location purposes. need. In one embodiment, the LMU is essentially a receiver with computational capabilities. As a further example, an LMU receiver utilizes SDR (Software Defined Radio) technology. In further embodiments, the LMU may be a small cell, a macro cell, or a special purpose small cell type device that only receives.

Regardless of the implementation, correlation of the SRS location for a particular UE, as provisioned by the network, enables identification and location of the UE. SRS location may be done at the network level or within a local sector, such as a DAS for a building, a small cell, or a combination of small and macro cells serving a particular area. If the SRS location for the UE is not known a priori, a solution may be able to correlate the UE's location throughout the coverage area. Such correlation shows the history of where the UE has moved. In some situations, it may be desirable for the network to determine the UE's location even if the SRS does not provide an indication of where the particular UE is located. A UE's location may be correlated with SRS by determining the UE's location or proximity relative to a known point, thereby correlating the UE with the SRS it is transmitting. Such localization can be accomplished through other location/nearby resolutions, such as Wi-Fi and Bluetooth®. Users may also identify their location via the UE application or by walking to a predetermined location to identify their UE for location resolution.

11 and 27 only macro base stations are shown. FIG. 27 also depicts the LMU co-located with the base station. These depictions are valid options, but the LTE standard does not prescribe where LMUs can be placed, as long as the LMU placement meets multilateration/trilateration requirements.

In an aspect, common deployments for indoor environments are DAS (Distributed Antenna Systems) and/or small cells, which are highly RF integrated and inexpensive base stations. The LMU(s) may be deployed in indoor and/or campus-type environments as well, eg, U-TDOA may be used in DAS and/or small cell environments. In another aspect, U-TDOA-based accurate indoor positioning uses a combination of indoor-located LMUs and outdoor-located macrocells, e.g., without the need to deploy DAS and/or small cells. or may have a reduced number of small cells. Therefore, LMUs may be deployed with or without the presence of DAS and/or small cells. In a further aspect, the LMU may be deployed in environments where cellular signal amplifiers/boosters are used, with or without the presence of DAS and/or small cells.

LTE Release 11 also contemplates integration of LMU and eNB into a single unit. However, this is a small, unprepared area for wireless/cellular service providers to meet, especially when individual small cell eNBs are geographically distributed, especially in indoor and/or other GPS/GNSS-denial environments. It further burdens the time synchronization requirements between cells.

DAS systems are inherently time-synchronized to a much higher degree (accuracy) than geographically dispersed macro/mini/small cell/LMUs. Using the DL-DTOA solution alleviates the time synchronization problem in a DAS environment, but in a DAS environment multiple antennas carry the same downlink signal with the same cell ID (identification number), A single base station serves multiple distributed antennas. As a result, the traditional DL-OTDOA approach fails because there are no identifiable neighboring cells (antennas) generating signals with different IDs. Nevertheless, using DL-OTDOA techniques when utilizing multipath mitigation processors and multipath mitigation techniques/algorithms as described in US Pat. , MULTI-PATH MITIGATION IN RANGE FINDING AND TRACKING OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY, which can extend the use of location integrity algorithm(s) such as those described in US Pat. The entirety is incorporated herein by reference. However, these matching algorithms are limited in the number of antennas emitting signal(s) with the same ID. One solution is to reduce the number of antennas emitting the same ID, eg, distribute multiple DAS antennas into two or more time-synchronized clusters with different IDs. Such a deployment increases system cost (increases the number of base stations) and requires handsets/UEs to support the technologies described above.

Utilizing U-TDOA within a DAS environment also adds costs associated with adding/installing LMU units. However, no changes to the UE (handset) are required, only the base station software needs to be upgraded to support the U-TDOA functionality. Also, multiple LMUs can be (into) integrated with a DAS system. Therefore, the use of the U-TDOA method with LMUs has many advantages when used indoors, in campus environments, and in other GPS/GNSS harsh, geographically confined environments.

Precise time synchronization among geographically distributed base stations and/or small cells and/or LMUs in indoor and other GPS/GNSS-rejected environments can be achieved by macrocells and/or outdoor macrocells, e.g., GPS It is more complex than time synchronization of LMU equipment used in /GNSS friendly environments. This is because macrocells in outdoor environments have antennas that are elevated and outdoors. As a result, the GPS/GNSS signal(s) quality is very good, and the macrocell antenna transmission and/or LMU receiver uses GPS/GNSS over a sufficiently large area with very high accuracy, That is, it can be synchronized up to a standard deviation of 10 ns.

In certain aspects, for indoor and other GPS/GNSS-rejected environments, time synchronization among multiple distributed base stations and/or small cells/LMUs may require many base stations and/or small cells and/or or by using an external sync source that generates a sync signal shared by the LMUs. This synchronization signal may be derived from GPS/GNSS, eg, 1PPS signals, and/or Internet/Ethernet networking, eg, PTP or NTP, or the like. The latter is a low-cost solution, but it cannot provide the required time synchronization accuracy for precise localization, and the GPS/GNSS-derived external synchronization signal(s) , is more precise, with standard deviations down to 20 ns, but requires additional hardware and installation requirements, such as wiring these signals, and is more complicated/expensive. Also, changes to the base station and/or small cell hardware/low level firmware may be required to adapt the external synchronization signal to higher levels of accuracy. Furthermore, a standard deviation of 20 ns is not accurate enough to meet the 3 meter requirement, eg, a standard deviation of about 10 ns.

To overcome the limitations described above, one embodiment uses an LMU device 2800 with multiple receive antennas 2802 and signal channels 2804, as illustrated by the multi-channel LMU high-level block diagram of FIG. As an example, one or more signal channels 2804 may include signal processing components such as an RF front end (RFE) 2806, an RF downconverter 2808, and/or an uplink location processor 2810. Other components and configurations may be used. In an aspect, the signal channels 2804 are co-located within the LMU device 2800 and closely time-synchronized (eg, standard deviation of about 3 ns to about 10 ns). In another embodiment, antennas 2802 from each LMU signal channel 2804 are geographically dispersed (eg, similar to DAS). As a further example, an external time synchronization component (eg, GPS/GNSS, Internet/Ethernet, etc.) may communicate with LMU device 2800 . Precise time synchronization is more easily achieved inside a device (eg, LMU device 2800) than by trying to closely synchronize several geographically dispersed devices.

As an example, when two or more multi-channel LMUs (e.g., LMU device 2800) are deployed, time synchronization between these LMUs is a low-cost and low-complexity approach (using external source signals ) can be relaxed so that it can be used to synchronize several distributed multi-channel LMUs. For example, Internet/Ethernet networking synchronization may be used, or a common sensor (device) may be deployed to provide timing synchronization between different multi-channel LMUs.

On the other hand, the multi-channel LMU approach reduces the number of hyperbolic lines of position (LOPs) that can be used in determining position fix, but improved time synchronization fills this gap (see discussion below and examples). overcome.

測定の正確性（非特許文献７を参照）と相関している。すなわち、

Using the multilateration/trilateration method, the UE positioning accuracy is affected by two factors: Geometric Accuracy Loss (GDOP) due to the geometric arrangement of macrocell towers/small cells/LMUs , and single ranging

It correlates with measurement accuracy (see Non-Patent Document 7). i.e.

GDOP is correlated with the geographical dispersion of transmit antennas (for DL-OTDOA) or receive antennas (for U-TDOA). In the case of regularly spaced antennas, the two-dimensional GDOP estimate is equal to 2/√N (HB LEE, ACCURACY LIMITATIONS OF HYPERBOLIC MULTILATION SYSTEMS, 1973). where, for cellular networks, N is the number of emitters (macrocell tower/small cell/DAS antennas) 'audible' by the UE (for DL-OTDOA) or UE uplink transmissions (for U-TDOA) ) is the number of LMU/LMU receive channels that can "listen". Therefore, the standard deviation of the UE position error can be calculated as follows.

（６．７メートル）
であり、ここで、σ_ＳＹＮＣが、外部時間同期信号標準偏差（２０ｎｓ）であることを仮定する。この場合（Ｎ＝８）では、単一レンジング測定及びＵＥ位置誤差の標準偏差σ_ＰＯＳが、４．７４メートルに等しい。 Eight geographically (indoor) distributed (regularly spaced) single-receive-channel LMUs are detecting UE uplink transmissions, and these LMUs provide a 1PPS signal (e.g., 20ns standard deviation). In this case N=8 and there are 7 independent LOPs that can be used for UE position determination. Furthermore, the ranging error standard deviation, σ _R is 3 meters (about 10 ns), then the accuracy of a single ranging measurement is

(6.7 meters)
, where σ _SYNC is assumed to be the external time synchronization signal standard deviation (20 ns). In this case (N=8), the standard deviation σ _POS of the single ranging measurement and UE position error is equal to 4.74 meters.

As an example, if two, four receive channel LMUs (e.g., multi-channel LMU device 2800) with regularly spaced distributed antennas are detecting UE uplink transmissions, each An LMU produces a set of 3 closely time-synchronized LOPs (eg, about 3 ns standard deviation), and for 3 independent LOPs, N=4. In this case, two UE position fixes are generated, each with a standard deviation error σ _POS of 3.12 meters. Combining these two position fixes by averaging and/or other means/methods further reduces the UE position fix error. One estimate is that the error reduction is proportional to the square root of the number of UE position fixes. In this disclosure, this number equals 2 and the final UE position fix error σ _{POS_FINAL} is 2.21 meters, taken as 3.12/√2.

In certain aspects, several multi-channel LMUs (eg, LMU device 2800) may be used for indoor and other GPS/GNSS-rejected environments, with relaxed synchronization between these multi-channel LMUs. As an example, within a multi-channel LMU device, the LMUs can be closely synchronized (eg, standard deviation of about 3 ns to about 10 ns). Another embodiment is that several single-channel small cells/LMUs and/or small cells with integrated LMU device electronics (LMU functionality embedded in the eNB) are mounted in a rack-mount enclosure (FIGS. 31, 32). , and FIG. 33) and/or take advantage of the fact that they can be clustered (eg, integrated, co-located, etc.) within a cabinet, eg, a 19″ rack. Each single-channel device antenna may be geographically distributed as in a DAS. Devices within a cluster can be closely time-synchronized (eg, standard deviation of 10 ns or less). Multiple rackmount enclosures can be synchronized per communication requirement, eg VoLTE, whereby a low cost and low complexity approach can be used. Precise (rigorous) time synchronization between several devices clustered (integrated) inside a rackmount enclosure/cabinet to closely time-synchronize several geographically dispersed devices more easily accomplished and less expensive than

Alternatively, multiple LMUs may be integrated with (into) the DAS system as illustrated in FIG. As an example, the LMU receivers may share the received signal(s) generated by each DAS antenna, eg, share the DAS antennas. The actual distribution of these received signals depends on the DAS implementation, active versus passive DAS. However, the combined LMU and DAS embodiment shares the received signal(s) generated by each DAS antenna with the LMU receiver channel and each DAS antenna coordinate with the corresponding LMU/LMU receiver channel. Generating matching (correlating) almanacs. Again, clustering approaches and/or utilization of multi-channel LMU(s) are preferred approaches for LMU and DAS integration.

Also, in a similar manner, the received signal(s) generated by each small cell antenna with an LMU receiver channel can be shared. Here, the small cell time synchronization may be relaxed, e.g., it does not have to meet the location requirements, while the LMU/LMU channel requires high precision time synchronization. A clustering approach and/or the use of multi-channel LMU(s) are the preferred LMU(s) approaches for such options.

Integrating the LMU and eNB into a single unit has a cost advantage over the combination of standalone eNB and LMU devices. However, unlike the integrated LMU and eNB receiver, the standalone LMU receive channel does not need to process the data payload from the UE. Furthermore, since the UE uplink ranging signal (SRS, Sounding Reference Signal in the case of LTE) is repeatable and time-synchronized (with respect to the serving cell), each standalone LMU receive channel has 2 It may support (and be time multiplexed with) more than one antenna, and may serve, for example, more than one small cell. This in turn can reduce the number of LMUs (in small cell/DAS and/or other U-TDOA location environments) and reduce system cost (see also FIG. 28).

If the wireless/cellular network E-SMLC server lacks the functionality required for the DL-OTDOA and/or U-TDOA techniques, this functionality is located where it can communicate with the UE and/or LMU. It may be performed by a specific service server and wireless/cellular network infrastructure and/or location server (see Figures 29 and 30). Other configurations may be used.

In another aspect, one or more LMU devices (eg, LMU 2802) may be deployed using a WiFi infrastructure, eg, as illustrated in FIG. Instead, listening devices can be used to monitor the LMU antenna in the same manner as the WiFi infrastructure. As such, LMU devices and/or channel antennas serving LMUs may be co-located with one or more WiFi/listening devices 3500, such as one or more WiFi access points (APs). As an example, WiFi devices 3500 may be geographically distributed.

In one embodiment, WiFi device 3500 may be connected to a power source. The RF analog portion 3502 (eg, circuitry) of one or more LMU devices or channels may be integrated with the LMU antenna such that the RF analog portion 3502 shares power with the WiFi device 3500 (see FIG. 35). As an example, the RF analog portion 3502 of the LMU device or channel can be connected via a cable to an uplink location processor circuit (eg, uplink location processor 2810), which can include baseband signal processing. can. As a further example, between the RF analog portion 3502 and the baseband circuitry, there may be signal amplification between the antenna and interconnecting cables, such embodiments facilitate improved signal-to-noise ratio (SNR). to Moreover, the RF analog portion 3502 can downconvert the received signal (e.g., to baseband), and since the baseband signal frequency is somewhat smaller in magnitude than the received signal at the antenna, cable requirements can be mitigated. Such relaxation of cable requirements can reduce connection costs and can significantly increase transmission distances.

It is understood that the ranging signal is not limited to SRS only, but can utilize other reference signals including MIMO, CRS (cell specific reference signal), etc.

Thus, having described different embodiments of systems and methods, it should be apparent to those skilled in the art that certain advantages of the described methods and apparatus have been realized. In particular, it will be appreciated by those skilled in the art that a system for tracking and locating objects can be constructed using a combination of FGPA or ASIC and standard signal processing software/hardware at very small cost increments. should be. Such systems are useful in a variety of applications, such as locating humans in hostile and hostile environments, such as in indoor or outdoor environments.

It should also be recognized that various modifications, adaptations, and alternative embodiments thereof may be made within the scope and spirit of the invention.

Claims (11)

A method for determining the location of one or more mobile communication devices within a wireless system, comprising:
The method includes receiving a reference signal from or transmitted to one mobile communication device via a plurality of geographically distributed antennas, each received reference The signal is then transmitted to a stationary location management unit having two or more co-located channels, said two or more co-located channels each comprising hardware and software components, said two or more are time synchronized to each other by an external synchronization source generating a time synchronization signal shared between said two or more co-located channels, the location of each antenna associated with said location management unit being known and
The method further comprises calculating the location of the mobile communication device utilizing the received reference signal at each location management unit. 2. The method of claim 1, wherein each of said two or more co-located channels is a location management unit card or within a base station of a small cell. 2. The method of claim 1, wherein each of the two or more co-located channels are integrated with the same rack mount system. 2. The method of claim 1, wherein the co-located channels are synchronized within a standard deviation of a predetermined time based on the desired accuracy of the location for the wireless system. 5. The method of claim 4, wherein said predetermined time is 10 ns or less. 2. The method of claim 1, wherein utilizing the received reference signals comprises utilizing one or more lines of position (LOPs). 2. The method of claim 1, wherein the geographically distributed plurality of antennas are the geographically distributed plurality of mobile communication devices. 2. The method of claim 1, wherein each of said plurality of geographically dispersed antennas is a shared group of antennas communicating with said two or more co-located channels. 2. The method of claim 1, wherein the location management unit or an antenna serving the location management unit is co-located with a WiFi device. 10. The method of claim 9, wherein the location management unit shares power with the WiFi device. 10. The method of claim 9, wherein the antenna serving the location management unit shares power with the WiFi device.

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