JP2017531934A - Partially synchronized multi-side / tri-side survey method and system for position finding using RF - Google Patents

Abstract

A system and method for determining the location of one or more user equipments (UEs) in a wireless system includes a reference signal via a location management unit having two or more co-located channels that are closely synchronized with each other. Receiving and calculating a location of at least one UE among the one or more UEs using the received reference signal. Embodiments include multi-channel synchronization with a standard deviation of 10 ns or less. Embodiments can include two LMUs, where each LMU has internal synchronization or one LMU is closely synchronized with the signal.

Description

  This embodiment is for radio frequency (RF) based identification, tracking, and location of objects, including wireless communication and wireless network systems, and RTLS (Real Time Location Service) and LTE based location services. About the system.

CROSS REFERENCE TO RELATED APPLICATIONS This application is a US Provisional Patent Application No. 37, filed on August 1, 2014, entitled PARTIALLY SYNCHRONIZED MULTILATERATION / TRILATIONATION METHOD AND SYSTEM FOR POSITIONAL FINDING USING RF No. 62 US Patent Application No. 13 / 566,993, filed on August 3, 2012, which is also filed on August 3, 2012, entitled MULTI-PATH MITIGATION IN RANGING FINDING AND TRACKING OBJECTS USING REDUCED ATTENUTION RF TECHNOLOGY Yes, this US patent application is MULTI-PATH MITIGATION IN RANGE FINDING AND TRACKING OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY TECHNO TRADE TRACK Entitled US Provisional Application No. 61 / 554,945, filed November 2, 2011, MULTI-PATH MITIGATION IN RANGE FINDING AND TRACKING OBJECTS USING REDUCED ATTENUTION RF TECHNOLOGY US Provisional Application No. 61 / 618,472, filed March 30, 2012, and MULTI-PATH MITIGATION IN RANGING FINDING AND TRACKING OBJECTS USING REDUCED ATTENUTION RF TECHNOLOGY U.S. Provisional Application No. 61 / 662,270, 35U. S. C. Claim the benefits under §119 (e), which are hereby incorporated by reference in their entirety.

  US Patent Application No. 13 / 566,993 is a US patent application filed on May 17, 2011 entitled MULTI-PATH MITIGATION IN RANGE FINDING AND TRACKING OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY This US patent application is filed on January 18, 2011, filed on January 18, 2011, entitled METHODS AND SYSTEM FOR MULTI-PATH MITIGATION IN TRACKING OBJECTS USING REDUCED ATTENUTION RF TECHNOLOGY. / 008,519 (currently issued on June 28, 2011 No. 7,969,311), which is a US application filed on July 14, 2009 entitled METHODS AND SYSTEM FOR REDUCED ATTENUATION IN TRACKING OBJECTS USING RF TECHNOLOGY. No. 12 / 502,809 (currently US Pat. No. 7,872,583 issued Jan. 18, 2011), this US patent application is METHODS AND SYSTEM FOR US patent application Ser. No. 11 / 610,595, filed Dec. 14, 2006 (currently entitled REDUCED ATTENUATION IN TRACKING OBJECTS USING RF TECHNOLOGY) Is a continuation of U.S. Pat. No. 7,561,048 issued on Jul. 14, 2009), and this U.S. patent application is entitled “METHOD AND SYSTEM FOR REDUCED ATTENUTION IN TRACKING OBJECTS USING MULTI-BAND RF TECHNOLOGY”. US Provisional Patent Application No. 60 / 597,649, filed December 15, 2005, 35U. S. C. Claims the benefits under §119 (e), which are incorporated herein by reference in their entirety.

  METHODS AND SYSTEM FOR REDUCED ATTENUATION IN TRACKING OBJECTS USING RF TECHNOLOGY, U.S. Patent Application No. 12 / 502,809, filed July 14, 2009, is also known as METHODS AND SYSTEM INT US Provisional Application No. 61 / 103,270, filed Oct. 7, 2008, entitled OBJECTS USING REDUCED ATTENUATION RF TECHNOLOGY. S. C. We also claim benefits under §119 (e), which are incorporated herein by reference in their entirety.

  RF-based identification and location discovery systems for determining the relative or geographical location of objects are commonly used to track single objects or groups of objects, as well as to track individuals. Conventional location systems are used for positioning 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 systems suffer from certain inaccuracies when locating objects in a closed (ie, indoor) environment as well as outdoors.

  Cellular wireless communication systems provide various ways of locating user equipment (UE) locations in an indoor and in a less suitable environment for GPS. The most accurate method is a positioning technique based on multi-sided / triangular surveying. For example, LTE (Long Term Evolution) standard release (Release) 9 defines DL-OTDOA (arrival time difference observed in downlink: Downlink Observed Time Difference of Arrival). The U-TDOA (Uplink Time Difference of Arrival) technique, which is a derivative of the surveying / triangulation method, is defined.

  Since time synchronization errors affect location accuracy, the basic requirement for a multi-sided / triangulation-based system is a complete and precise time synchronization of the system to a single common reference time. In cellular networks, DL-OTDOA and U-TDOA location methods are also used in DL-OTDOA, where transmissions from multiple antennas are time-synchronized, or in U-TDOA, multiple receivers. Requires that they be time synchronized.

US Pat. No. 7,561,048 US Pat. No. 5,525,967 US Pat. No. 7,872,583 US Patent Application Publication No. 2008/0285505 International Publication No. 2010/104436 US Patent Application Publication No. 2003/008156 U.S. Pat. No. 7,167,456 US Patent Application Publication No. 2010 / 0091826A1 US Patent Application Publication No. 2011 / 0124347A1 Specification US Pat. No. 7,969,311 US Pat. No. 8,305,215 US Non-Provisional 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 Estimator 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 Interior Localization System” Gunter Seeber, “Satelite Geodesy”, 2003

  LTE Standard Release 9 and Release 11 do not specify time synchronization accuracy for location purposes, and leave this to the wireless / cellular service provider. On the other hand, these standards place 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. is there.

  The above limitations are the result of a combination of ranging measurement errors and errors caused by the lack of precision 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 evenly distributed . One such estimate would be 200ns (100ns from peak to peak). Note that the Voice over LTE (VoLTE) function also requires cellular network synchronization to be reduced to 150 nanoseconds (75 ns from peak to peak), assuming that the synchronization error is evenly distributed. . Therefore, from now on, it is assumed that the accuracy of time synchronization of the LTE network is within 150 ns.

  With regard 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 positioning error introduced by the 150 ns time synchronization error (43 ns standard deviation) is much greater than the 3 meter ranging error (10 ns standard deviation).

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

  The present disclosure provides radio frequency (RF) -based identification, tracking, and location of objects, including a real-time location service (RTLS) system that substantially eliminates one or more of the disadvantages associated with existing systems. The present invention relates to a method and a system. The method and system may use a receiver and / or transmitter that is partially synchronized (in time). According to certain embodiments, RF-based tracking and localization is implemented in a cellular network, but can also be implemented in any wireless system and RTLS environment. The proposed system can use digital signal processing implemented in software and software defined radio technology (SDR). Digital signal processing (DSP) can be used as well.

  While one approach described herein utilizes a cluster of receivers and / or transmitters that are precisely time synchronized within each cluster, intra-cluster time synchronization may be significantly less accurate. There may or may not be required at all. This embodiment may be used in all wireless systems / networks and may include simplex, half duplex, and full duplex operating modes. 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 using an LTE network and can be applied to other wireless systems / networks.

  As described in one embodiment, RF-based tracking and localization implemented on a 3GPP LTE cellular network significantly benefits the benefits of a precisely (time-synchronized) receiver and / or transmitter cluster. receive. The proposed system can use digital signal processing implemented in software and / or hardware.

  Additional features and advantages of the embodiments will be defined in the description that follows, and will be in part apparent from the description, or may be learned by practice of the embodiments. The advantages of the embodiments are 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.

FIG. 5 illustrates a narrow bandwidth ranging signal frequency component, according to an embodiment. FIG. FIG. 5 illustrates a narrow bandwidth ranging signal frequency component, according to an embodiment. FIG. 2 illustrates an exemplary wide bandwidth ranging signal frequency component. FIG. 3 illustrates a block diagram of a master and slave unit of an RF mobile tracking and location system, according to an embodiment. FIG. 3 illustrates a block diagram of a master and slave unit of an RF mobile tracking and location system, according to an embodiment. FIG. 3 illustrates a block diagram of a master and slave unit of an RF mobile tracking and location system, according to an embodiment. Fig. 4 illustrates an embodiment of a synthesized wideband baseband ranging signal. FIG. 4 illustrates the removal of a signal precursor by cancellation, according to an embodiment. FIG. Fig. 6 illustrates preceding wave cancellation with fewer carriers, according to an embodiment. 3 illustrates an embodiment with a unidirectional transfer function phase. 1 illustrates one embodiment of a location method. 3 illustrates an LTE reference signal mapping. Fig. 4 illustrates an embodiment of an enhanced cell ID + RTT location technique. 3 illustrates one embodiment of an OTDOA location technique. FIG. 4 illustrates the operation of a time observation unit (TMO) installed in an operator's eNB facility, according to an embodiment. 2 illustrates an embodiment of a wireless network location device diagram. Fig. 3 illustrates an embodiment of a wireless network location downlink ecosystem for enterprise use. FIG. 4 illustrates an embodiment of a wireless network location downlink ecosystem for use across a network. FIG. 2 illustrates one embodiment of a wireless network location uplink ecosystem for enterprise use. 1 illustrates one embodiment of a wireless network location uplink ecosystem for use across a network. Fig. 4 illustrates an embodiment of a UL-TDOA environment that may include one or more DAS and / or femto / small cell antennas. 19 illustrates an embodiment of UL-TDOA similar to that of FIG. 18 that may include one or more cell towers that may be used in place of a DAS base station and / or femto / small cell. Figure 3 illustrates an embodiment of cell level location. Fig. 4 illustrates an embodiment of serving cell and sector ID location. The embodiment which added AoA position specification to E-CID is illustrated. Figure 3 illustrates one embodiment of AoA location. Fig. 4 illustrates an embodiment of TDOA using wide open and close distances between receive antennas. 2 illustrates an embodiment of a three sector deployment. 3 illustrates an embodiment of antenna port mapping. 3 illustrates one embodiment of an LTE release 11U-TDOA location technique. FIG. 4 illustrates an embodiment of a high level block diagram of a multi-channel location management unit (LMU). Fig. 4 illustrates an embodiment of DL-OTDOA technique in a wireless / cellular network using a location server. Fig. 3 illustrates an embodiment of U-TDOA technique in a wireless / cellular network with a location server. Fig. 4 illustrates an embodiment of a depiction of a rack mount housing. FIG. 6 illustrates an embodiment of a high level block diagram of multiple single channel LMUs clustered (integrated) in a rack mount enclosure. FIG. 6 illustrates an embodiment of a high-level block diagram of multiple small cells with integrated LMUs clustered (integrated) in a rack mount enclosure (one-to-one antenna connection / mapping). Figure 3 illustrates an embodiment of a high level block diagram of an integrated LMU and DAS. FIG. 3 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, 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 the preferred embodiments of the present embodiments, examples of which are illustrated in the accompanying drawings.

  This embodiment relates to a method and system for RF-based identification, tracking, and localization of objects, including RTLS. According to certain embodiments, the method and system utilize a narrow bandwidth ranging signal. 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 frequencies. It utilizes a multipath mitigation processor. The use of a multipath mitigation processor increases the tracking and localization accuracy achieved by the system.

  Embodiments include a small, highly portable base unit that allows a user 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 send 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, depending on the triangulation or triangulation method and / or other methods used, continuously their relative and / or actual location. To decide. Preferred embodiments can also be easily integrated with products such as, for example, GPS devices, smart phones, two-way radios, and PDAs. The resulting product has all of the capabilities of a stand-alone device while leveraging the existing display, sensors (eg, altimeter, GPS, accelerometer, and compass), and the processing power of its host. For example, a GPS device using the device technology described herein can not only provide a user's location on a map, but can also map the location of other members of the group.

  The preferred embodiment size based on FPGA implementation is about 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 the unit or tag. ASIC-based stand-alone products result in device sizes of 1 × 0.5 × 0.5 inches or less. The antenna size is determined by the frequency used and the portion of the antenna can be integrated into the housing. An ASIC-based embodiment is designed to be integrated into a product and can only consist of a chipset. There should be no substantial physical size difference between master or tag units.

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

  U.S. Pat. No. 6,057,031 discloses a narrow bandwidth ranging signal system, whereby narrow bandwidth ranging signals can only be, for example, a few kilohertz (although some of the low bandwidth channels can span tens of kilohertz). Is designed to accommodate low bandwidth channels using a voice channel that is a wide bandwidth. This is in contrast to conventional location systems that use channels from hundreds of kilohertz to tens of megahertz wide.

  The advantages of this narrow bandwidth ranging signal system are as follows. That is, 1) At low operating frequencies / bands, the ranging signal bandwidth of a conventional location system exceeds the carrier (operating) frequency value. Therefore, such a system cannot be deployed in LF / VLF and other lower frequency bands, including HF. Unlike conventional location discovery systems, the narrow-bandwidth ranging signal system described in US Pat. No. 6,057,086 is successful on LF, VLF, and other bands because its ranging signal bandwidth is well below the carrier frequency value. Can be deployed on the back. 2) For example, at the lower end of the RF spectrum (some VLF, LF, HF, and VHF bands) up to the maximum UHF band, the FCC severely limits the allowable channel bandwidth (12-25 kHz) Conventional location systems cannot be used because they render the ranging signal unusable. Unlike conventional location discovery systems, the ranging signal bandwidth of narrow bandwidth ranging signal systems is fully compliant with FCC regulations and other international spectrum regulatory agencies. 3) It is well known that independent of the operating frequency / band, a narrow bandwidth signal has an inherently high SNR (signal to noise ratio) compared to a wide bandwidth signal (see Non-Patent Document 1). ). This increases the operating range of the narrow bandwidth ranging signal location discovery system, independent of the frequency / band in which it operates, including the UHF band.

  Therefore, unlike conventional location systems, narrow bandwidth ranging signal location systems are more sensitive to VHF and lower frequency bands up to the RF spectrum, e.g., LF / VLF bands, where multipath phenomena are less pronounced. Can be deployed on the lower end of the. At the same time, the narrow bandwidth ranging location discovery system can also be deployed on and above the UHF band, improving the ranging signal SNR and consequently increasing the operating range of the location discovery system.

  It is desirable to operate on the VLF / LF band to minimize multipath, eg, RF energy reflection. However, at these frequencies, the efficiency of the portable / mobile antenna is very small (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 anthropogenic sources are significantly higher than those on high frequencies / bands such as VHF. Both of these two phenomena can limit the applicability of a location discovery system, for example its range of operation and / or mobility / portability. Thus, 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, the noise level from natural and anthropogenic sources is significantly lower compared to the VLF, LF, and HF bands, and at VHF and HF frequencies, multipath phenomena (eg, RF energy reflection) And less severe than at higher frequencies. Also, with VHF, the antenna efficiency is significantly better than at HF and lower frequencies, and with VHF, the RF penetration capability is much better than at UHF. Therefore, the VHF band provides a good compromise for mobile / portable applications. On the other hand, UHF may be a good option in some special cases, for example in GPS where VHF frequencies (or lower frequencies) cannot penetrate (or be deflected / refracted) the ionosphere. However, in any case (and in all cases / applications), the narrow bandwidth ranging signal system is advantageous over the conventional wide bandwidth ranging signal location discovery system.

  The actual application (s) will determine the exact technical specifications (eg, power, radiation, bandwidth, operating frequency / band, etc.). Narrow bandwidth ranging allows a user to receive a license or receive a license exemption, or to use a band that is not licensed as defined in the FCC. This is because narrowband ranging can operate over many different bandwidths / frequency, including the most stringent narrowband as defined by the FCC, ie 6.25 kHz, 11.25 kHz, 12.5 kHz, 25 kHz, and 50 kHz. Because it complies with the corresponding technical requirements for the appropriate section. As a result, multiple FCC sections and exemptions within such sections are applicable. The main applicable FCC regulations are 47CFR Part90-Private Land Mobile Radio Services, 47CFR Part94 personal Radio Services, 47CFR Part15-Radio Frequency Devices. (By comparison, wideband signals in this context are from a few hundred KHz up to 10-20 MHz)

  Typically, for Part 90 and Part 94, the VHF implementation allows the user to operate the device up to 100 mW under certain exemptions (low power wireless communication service is an example). For certain applications, the allowable transmitted power in the VHF band is 2-5 watts. For 900 MHz (UHF band) it is 1W. On the 160 kHz to 190 kHz frequency (LF band), the allowable transmitted power is 1 watt.

  Narrowband ranging can comply with many if not all of the different spectral tolerances and allows accurate ranging while still complying with the most stringent regulatory requirements. This applies not only to the FCC, but also to other international organizations that regulate spectrum use throughout the world, including Europe, Japan, and Korea.

  The following is a list of common frequencies used, with typical power usage and distance, 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 the VHF frequency and utilizes a proprietary method for transmitting and processing RF signals. More specifically, it overcomes the limitations of narrow bandwidth requirements at VHF frequencies using DSP techniques and software defined radio (SDR).

  Operation at lower (VHF) frequencies reduces scatter and results in a much better wall penetration. The net result is an increase of about 10 times over the commonly used frequencies. For example, compare the measured range of the prototype with that of the RFID technology listed above.

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

  Utilizing narrowband ranging techniques significantly increases the range of commonly used frequencies, and with typical power usage and distance, tag coverage can be used by other readers in a real-world environment. It becomes possible to communicate with.

――――――――――――――――――――――――――――――――――――
From 915MHz 100mW 150 feet 500 feet 2.4GHz 100mW 100 feet 450 feet 5.6Ghz 100mW 75 feet 400 feet ――――――――――――――――――――――――― ――――――――――

  Battery consumption correlates with 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 to 1000X. For applications using a large duty cycle, eg 100X, an FPGA version carrying 100 mW of power has an uptime of about 3 weeks. The ASIC-based version is expected to increase uptime by a factor of ten. ASICs also have inherently lower noise levels. Therefore, the ASIC-based version can also increase the operating range by about 40%.

  One skilled in the art will recognize that embodiments significantly increase the accuracy of location discovery in RF harsh environments (eg, buildings, urban corridors, etc.), while not compromising the long operating range of the system.

  Typically, tracking and locating systems utilize tracking-localization-navigation methods. These methods include time of arrival (TOA), time difference of arrival (DTOA), and a combination of TOA and DTOA. The time of arrival (TOA) as a distance measurement technique is generally described in US Pat. A TOA / DTOA based system measures the direct line-of-sight (DLOS) flight time, eg, time delay, of the RF ranging signal, which is then converted to a distance range.

  In the case of RF reflection (eg, multipath), multiple copies of the RF ranging signal with various delay times are superimposed on the DLOS RF ranging signal. Tracking-positioning systems that use 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 flight time, which in turn affects the accuracy of the range estimation.

  Embodiments advantageously use a multipath mitigation processor to separate DLOS and reflected signals. Therefore, embodiments significantly reduce errors in the estimated ranging signal DLOS flight time. The proposed multipath mitigation method can be used on all RF bands. It can also be used with a wide bandwidth ranging signal location discovery system. Moreover, it can support various modulation / demodulation techniques including spread spectrum techniques such as DSS (direct spread spectrum) and FH (frequency hopping).

  In addition, noise reduction methods may be applied to further improve the accuracy of the method. These noise reduction methods can include, but are not limited to, coherent addition, incoherent addition, 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 (such as the Viterbi algorithm as an example), minimum variance estimation (Kalman filter), and the like.

  Embodiments may be used in systems that use simplex, half duplex, and full duplex operating modes. Full-duplex operation requires a great deal in terms of complexity, cost, and logistics associated with RF transceivers, which limits the system operating range in portable / mobile device implementations. In half-duplex mode of operation, a reader (often referred to as a “master”) and a tag (sometimes also referred to as a “slave” or “subject”), the master or slave is arbitrarily given. It is controlled by a protocol that allows transmission only during a certain time.

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

  In this embodiment, the narrow bandwidth ranging signal multipath mitigation processor does not increase the ranging signal bandwidth. It advantageously allows the propagation of narrow bandwidth ranging signals using different frequency components. Further ranging signal processing assembles the synthesized ranging signal with a relatively large bandwidth in the frequency domain by utilizing a super-resolution spectral estimation algorithm (MUSIC, rootMUSIC, ESPRIT) and / or statistical algorithms such as RELAX Thus, further processing can be performed in the time domain by applying this signal. Different frequency components of the narrow bandwidth ranging signal can be selected pseudo-randomly, which can also be continuous or spaced apart in frequency, which has uniform and / or non-uniform spacing in frequency be able to.

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

  The frequency separation between the direct path and the 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 step rate of 100 KHz over 5 MHz in the range of 30 meters (100.07 nanosecond delay) results in a frequency of 0.062875 radians / second. 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 observables has an inherent frequency resolution of 0.12566 Hz. As a result, the direct path range cannot be accurately estimated using conventional frequency estimation techniques for 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 methodology and multimodal cluster analysis implementations. Subspace decomposition techniques rely on dividing the estimated covariance matrix of observed data into two orthogonal subspaces, a noise subspace, and a signal subspace. The theory behind the subspace decomposition methodology is that the observable projection onto the noise subspace consists only of noise and the observable projection onto the signal subspace consists only of signals.

  The super-resolution spectral estimation algorithm and the RELAX algorithm can distinguish frequencies (sinusoidal waves) located close in the spectrum in the presence of noise. The frequencies do not have to be in a harmonic relationship, and unlike the digital Fourier transform (DFT), the signal model does not introduce any artificial periodicity. For a given bandwidth, these algorithms provide 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 below to an artificially created synthetic wide bandwidth ranging signal allows 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, ie, multiple signal characterization (MUSIC) algorithm or Root-MUSIC algorithm, signal parameter estimation (ESPRIT) with rotation invariant technique algorithm, Pisarenco harmonic decomposition ( PHD) algorithm, RELAX algorithm, etc.

  The above super-resolution algorithm works on the premise that the signal affecting the antenna cannot be sufficiently correlated. Therefore, performance is severely degraded in highly correlated signal environments that can be encountered in multipath propagation. Multipath mitigation techniques may include a pre-processing scheme called spatial smoothing. As a result, the multipath mitigation process can be computationally intensive and complex, i.e. increasing the complexity of the system implementation. Multipath mitigation with low system computer computational cost and implementation complexity can be achieved by using a super-resolution matrix bundle (MP) algorithm. The MP algorithm is classified as a non-search procedure. Therefore, it is less computationally complex and eliminates problems encountered in search procedures used for other super-resolution algorithms. Moreover, the MP algorithm is not sensitive to correlated signals, requires only a single channel estimate, and can estimate the delay 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 frequency complex exponents and their complex amplitudes. In the case of multipath, the received signal is as follows.

（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 transmitted signal, 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 subscripted so that propagation delays are considered in ascending order. As a result, in this model, τ ₀ indicates the propagation delay of the DLOS path. Obviously, the τ ₀ value is the most interesting because it is the smallest of all τ _K. The phase θ _K is usually assumed to be random from one measurement cycle to another using the uniform probability density function U (0,2π). Therefore, we assume that α _K = constant (ie, constant value).

The parameters α _K and τ _K are random time-varying functions that reflect the movement of people and equipment in and around the building. However, their rate of variation is very slow compared to the measurement time interval, so 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 characteristics, such as transmission and reflection coefficients. However, in the embodiment, the operating frequency changes only slightly. Therefore, it can be assumed that the parameters described above are 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。 Equation (1) is

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

In equation (2), the super-resolution estimate of (2π × τ _K ) and subsequently the τ _K value is based on the continuous frequency. In practice, there are a finite number of measurements. Therefore, the variable f is not continuous but rather discontinuous. Thus, 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 a discontinuous complex amplitude estimate (ie, measured value) at the discontinuous frequency f _n .

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 equation (3),

Can be interpreted as the amplitude and phase of a sinusoidal signal of frequency f _n after it has propagated through the multipath channel. Note that all spectral estimation-based super-resolution algorithms require complex input data (ie, complex amplitude).

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, for example

Can be converted into a complex signal (eg, an analytic signal). For example, such a transformation can be achieved by using a 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” cause problems with the Hilbert transform (or other method) implementation. In addition, the amplitude value (for example,

) Only is used, the number of frequencies estimated includes not only (2π × τ _K ) “frequency”, but also combinations thereof. In general, increasing the number of unknown frequencies affects the accuracy of the super-resolution algorithm. Therefore, reliable and accurate separation of the DLOS path 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。 The following is the complex amplitude in the presence of multipath

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

  In half-duplex mode of operation, the reader (often referred to as “master”) and the tag (also referred to as “slave” or “subject”) can be used by the master or slave at any given time. Is controlled by a protocol that allows transmission only to In this operation mode, the tag (target device) functions as a responder. 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, such as pseudorandom, spaced in frequency and / or time, or orthogonal, may also be used as long as the ranging signal bandwidth remains narrow. In FIG. 1, the period _Tf for all frequency components is long enough to acquire the ranging signal narrow bandwidth characteristics.

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

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

  The narrowband ranging mode provides accuracy in the form of instantaneous wideband ranging compared to wideband ranging while at the same time increasing the range in which this accuracy can be achieved. With fixed transmit power, this performance is achieved because 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 provides a good trade-off when very rapid ranging is not required, for example, for stationary and slowly moving objects such as walking or running humans.

  The master device and tag device are the same 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 control the tag device remotely. In this example depicted in FIG. 1, during the operation of the master (ie, reader), the multipath mitigation processor generates a ranging signal to the tag (s), and after a certain delay, the master / read. The machine receives a repeated ranging signal 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 multipath mitigation processor then compares the received ranging signal with that originally transmitted from the master and in the form of amplitude and phase for all frequency components f _n .

Determine the estimate. In equation (3),

Note that is defined for a one-way ranging signal trip. In an embodiment, the ranging signal performs a round trip. In other words, it moves in both directions from the master / reader to the subject / slave and back from the subject / slave to the master / reader. Therefore, this round trip signal complex amplitude received back to 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. According to an embodiment, the complex amplitude determination is derived from a master and / or tag receiver RSSI (Received Signal Strength Indicator) value.

Based on value. Phase value

Is obtained by comparing the baseband ranging signal phase received and returned by the reader / master with 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 errors. As shown above, the unidirectional amplitude

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

The value cannot be measured directly.

In an embodiment, the ranging baseband signal is the same as depicted in FIG. However, for the sake of brevity, in this document, the ranging baseband signal will consist of only two frequency components, each containing multiple periods of cosine or sine waves of different frequencies F ₁ and F _2. Assumed. Note that F ₁ = f ₁ and F ₂ = f ₂ . The number of periods in the first frequency component is L, and the number of periods in the second frequency component is P. Note that L may or may not be equal to P. This is because when Tf = constant, each frequency component can have a different number of periods. Also, there is no time gap between each frequency component, and both F ₁ and F ₂ start from an initial phase equal to zero.

3A, 3B and 3C depict block diagrams of a master or slave unit (tag) of an RF mobile tracking and location system. F _OSC refers to the frequency of the device system clock (the crystal oscillator 20 in FIG. 3A). All frequencies generated in the device are generated from this system clock crystal oscillator. The following definitions are used: That is, M is a master device (unit), and AM is a tag (target) device (unit). The tag device operates in a responder mode and is referred to as an answering machine (AM) unit.

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

Because.

及び

に留意する。

as well as

Keep in mind.

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

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

Since the frequency of the crystal oscillator can be different from 20 MHz, the actual frequencies generated by the FPGA are F ₁ γ ^M and F ₂ γ ^M. In addition, time _{T 1} becomes _{T 1 β} ^M, _{T 2} becomes _{T 2 β} ^M. _{Further, T 1, T 2, F} 1, F 2 , such as the one at ^{_{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 Yes, where it is assumed that both F ₁ T ₁ and F ₂ T ₂ are integers. That means that the initial phase of F ₁ and F ₂ is 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 clocks, the outputs of the master baseband I / Q DAC (s) 120 and 125 are as follows:

as well as

here,

as well as

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

  The master (M) and responder (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 of the RF front end. The transponder receives the signal and downconverts the received signal back using its RF front end mixer 85 (creating the first IF) and ADC 140 (creating the second IF).

  This second IF signal is then digitally filtered using a digital filter 190 in a responder RF back end processor to produce an RF back end quadrature mixer 200, digital I / Q filters 210 and 230, Digital quadrature oscillator 220, as well as adder 270, are used to further downconvert to a baseband ranging signal. This baseband ranging signal is stored in the responder'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 transponder then switches from RX to TX mode using the switch 15 on the RF front end and starts retransmitting the stored baseband signal after a certain delay t _RTX . Note that the delay is measured in the AM (responder) system clock. therefore,

It is. The master receives the transponder transmission and uses its RF back-end quadrature mixer 200, digital I and Q filters 210 and 230, and digital quadrature oscillator 220 (see FIG. 3C) to baseband the received signal. Downconvert back to 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. The amplitude value is derived from the RSS back block 240 of the RF back end.

In order to improve the estimation accuracy, it is always desirable to improve the SNR of the amplitude estimation from block 240 and the phase difference estimation from block 255. In a preferred embodiment, the multipath mitigation processor calculates amplitude and phase difference estimates for many time examples over the ranging signal frequency component period (T _f ). These values improve the SNR when averaged. The improvement in SNR may be an objective proportional to √N, where N is some example when 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 filter techniques over a period of time. Yet another approach is to sample the phase and amplitude of the received (ie, repeated) baseband ranging signal frequency components, and then sample the original (ie, by the master / reader) in I / Q format. Estimation by integrating over the period T ≦ T _f over the transmitted (baseband) ranging signal frequency components. Integration has the effect of averaging multiple instances of amplitude and phase in I / Q format. After that, the phase and amplitude values are from I / Q format

as well as

Can be converted to a format.

  Assume that at t = 0, under master multipath processor control, the master baseband processor (both in FPGA 150) initiates a baseband ranging sequence.

Here, T _f ≧ T ₁ β ^M.

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

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

Note that

をもたらす。 Similarly, transmitter circuit components 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:

RF signal from the master (M) experience a phase shift phi ^MULT that correlates with multipath phenomenon between the master and tag.

The φ ^MULTI value depends on the transmitted frequency, eg F ₁ and F ₂ . An answering machine (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, for example after 1 microsecond (corresponding to a flight of about 300 meters), when all the reflected signals arrive at the receiver antenna, the following formula applies:

  In the AM (responder) receiver in the first downconverter, element 85, the output, for example, the first IF, the phase of the signal is as follows.

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 receiver RF section (elements 15 and 60-85)

Note that does not depend on the system clock. After passing through the RF front end filter and amplifier (elements 95-110 and 125), the first IF signal is sampled by the RF back end ADC 140. It is assumed that the ADC 140 is undersampling the input signal (eg, the first IF). Therefore, the ADC also acts like a downconverter that creates a second IF. The first IF filter, amplifier, and ADC add propagation delay time. At the ADC output (second IF)

It is.

である。 In the FPGA 150, the second IF signal (from the ADC output) is filtered by the RF back-end digital filter 190, and a third down converter (ie, quadrature mixer 200, digital filters 230 and 210, and digital quadrature oscillator 220). ) Is further converted back to the baseband ranging signal, added in the adder 270, and stored in the memory 170. At the third downconverter output (ie, quadrature mixer):

It 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 does not depend on the system clock.

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

Keep in mind.

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

  In the master receiver, the signal from the responder goes through the same down-conversion process as in the responder receiver. The result is a baseband ranging signal that was first transmitted and recovered by the master.

である。 The first frequency component _{F 1,}

It is.

である。 For the second frequency component F2,

It 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。 Replace,

Where _{TD_M-AM} is the propagation delay through the master (M) and responder (AM) circuit.

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 mixer, including the ADC (s).
Also,

It is.

である。 For the first frequency component F1,

It is.

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

It is.

である。 For the second frequency component F2,

It is.

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

It is.

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

Where α is constant.

（５）
である。 The final phase equation is

(5)
It is.

となり、ここで、ｉ＝２、３、４・・・・・・・・・・・・・・、

に等しい。 From equation (5)

Where i = 2, 3, 4,...

be equivalent to.

は、

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

Is

It 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} . That is,

Where T _{LB_M} and T _{LB_AM} are 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 transponder 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 t _RTX value, _{TD_M-AM} can be determined, so that for a 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)
It becomes.

  From equation (6), it can be concluded that at the operating frequency (s) ranging signal (s), complex amplitude values can be determined 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。 Since the subspace algorithm is not sensitive to a constant phase offset, the initial phase value

Can be assumed to be equal to zero. If necessary,

The value (initial phase value) can be determined by determining TOA (time of arrival) using a 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 equation:

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 a preferred embodiment, the returned baseband ranging signal phase value

Is calculated by the arctangent block 250 of the multipath processor. To improve the SNR, the multipath mitigation processor phase comparison block 255 uses equation (6A) to generate a number of instances n (n = 2, 3, 4,... ···)about,

Are then averaged to improve the SNR.

Keep in mind.

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 responder (AM) system clocks can 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 along with the corresponding individual frequency components of the original (ie, transmitted by the master) and over the period T ≦ T _f It is also possible to estimate the phase and amplitude of the received ranging signal by integrating the resulting signals.

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 based on the complex amplitude value of the ranging signal received in I / Q format.

Is generated. Note that the individual frequency components of each baseband signal transmitted by the master need to be shifted by a time of _{TD_M-AM} . The combined operation has the effect of averaging multiple instances of amplitude and phase (eg, increasing SNR). Phase and amplitude values from I / Q format

as well as

Note that it can be converted to a 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。 From sampling, integration over a period of T ≦ T _f , and subsequent I / Q format

as well as

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

Although the ranging signal bandwidth is narrow, the frequency difference f _n −f ₁ can be relatively large, for example, about several megahertz. As a result, the receiver bandwidth needs to 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. In order to reduce the effective bandwidth of the receiver and improve the SNR, the received ranging signal baseband frequency components are adjusted by a digital narrow bandwidth filter adjusted for the individual frequency components of the received baseband ranging signal, It can be filtered by an RF back-end processor in FPGA 150. However, this large number of digital filters (the number of filters is equal to the number n of individual frequency components) places 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 the frequency component f ₁ and the other filter can be adjusted for all other frequency components, ie f ₂ : f _n . Examples of ranging signals are transmitted by the master. Each example consists of only two frequencies f ₁ : f ₂ ; f ₁ : f ₃ ... F ₁ : f _i ;... F ₁ : f _n . Similar approaches are also possible.

Note also that it is entirely possible to keep the baseband ranging signal components at only two (or one) that generate the remainder of the frequency components by adjusting the frequency synthesizer, eg, changing K _SYN. I want you to. It is desirable that the LO signal for the upconverter and downconverter mixer be generated using direct digital synthesis (DDS) techniques. For high VHF band frequencies, this can result in an undesirable burden on the transceiver / FPGA hardware. However, for lower frequencies this may be a useful approach. An analog frequency synthesizer can also be used, but can take additional time to stabilize after the frequency is changed. Also, in the case of an analog synthesizer, two measurements at the same frequency need to be made to eliminate the phase offset that can occur after a change in 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 in both the master (M) and responder (AM) system clocks, for example, T _{LB_AM} and t _RTX are counted in the responder (AM) clock. , T _{LB_M} is counted in the master (M) clock. However,

Both T _{LB_AM} and t _RTX are measured (counted) in the master (M) clock. This is an error

(7)
Bring.

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

  In a preferred embodiment, the master and responder unit (device) can synchronize clocks with any of the devices. For example, the master device can function as a reference. Clock synchronization is achieved by using a remote control communication channel, whereby the frequency of the temperature compensated crystal oscillator TCXO 20 is adjusted 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 a carrier signal.

  The master then sends a command to the responder 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 be equal to zero. An alternative method is to measure the frequency difference and correct the estimated phase without adjusting the TCXO frequency of the responder.

Although β ^M -β ^AM can be significantly reduced, if β ^M ≠ 1, there is a phase estimation error. In this case, the error limit depends on the long-term stability of the reference device (usually master (M)) clock generator. In addition, in particular, the process of clock synchronization with multiple units in the field can take a significant amount of time. During the synchronization process, the tracking-location system becomes partially or completely inoperable, which adversely affects system preparation and performance. In this case, the above-described method that does not require the TCXO frequency adjustment of the responder is preferable.

  Commercial (in-stock) TCXO components have a high degree of accuracy and stability. Specifically, the TCXO component for GPS commercial applications is very accurate. With these devices, the effect 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。 Narrowband ranging signal multipath mitigation processor returns the narrowband ranging signal complex amplitude

Further processing (ie, execution of the 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 an 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) result in an estimate of (2π × τ _K ) “frequency”, eg, τ _K value. In the final step, the multipath mitigation processor selects τ (ie, DLOS delay time) having the minimum value.

  In certain cases where the ranging signal narrow bandwidth requirement is relaxed to some extent, the DLOS path can be separated from the MP path by utilizing a continuous chirp (in time). 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 duration of T is transmitted under multipath mitigation processor control. Every second

Give a radian char plate. Multiple chirps are transmitted and received back. Note that the chirp signal is generated digitally and each chirp starts at the same phase.

  In a multipath processor, each received single chirp is aligned 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 waveform equation is

Where ω ₀ is the initial frequency when 0 <t <T.
If there is no single delay round trip τ, eg, 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 “de-ramps” s (t−τ) by performing complex conjugate mixing with the originally transmitted chirp. The resulting signal is a complex sine wave

(8)
And
Here, 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 de-ramped composite signal consists of multiple complex sine waves.

(9)
Where L is the number of ranging signal paths, including DLOS paths, where 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 handled / processed individually as described above. The multipath mitigation processor then assembles the results of the individual chirp processes,

(10)
Where N is the number of chirps,

ρ = T + t _dead , t _dead is a _dead time zone between two consecutive chirps, and 2βτ _k is an artificial delay “frequency”. Again, what is most interesting 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 equation (10),

Is the time, ie

Can be considered as a total of N samples of the complex sine wave at. Therefore, the number of samples can be a plurality of N, eg, αN; α = 1, 2,.

  From equation (10), the multipath mitigation processor produces αN complex amplitude samples in the time domain used in further processing (ie, execution of the super-resolution algorithm). This further processing is implemented in a software component, which is part of a multipath mitigation processor. This software component may be executed by a master (reader) host computer CPU and / or by a microprocessor embedded in 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 an estimate of 2βτ _k “frequency”, eg, a τ _K value. In the final step, the multipath mitigation processor selects τ with the minimum value, ie DLOS delay time.

  A special processing method is described that can serve as an alternative to the super-resolution algorithm and is called a “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 wideband 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 a time domain baseband signal s (t), ie,

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

  FIG. 4 shows two periods of s (t) when 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 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 ranges 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 wideband ranging in distinguishing DLOS paths from other MP paths. is there. The threshold method detects when the beginning of the leading edge of a broadband pulse arrives at the receiver. Due to filtering at the transmitter and receiver, the leading edge does not rise instantaneously, but rises without noise with a smoothly increasing slope. The leading edge TOA 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 start of the pulse and exceeding the threshold is small. Therefore, any pulse replication that arrives 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 made. One way 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 a faster rise. Although higher order derivatives can be used, in practice they can raise the noise level to an unacceptable value, and therefore thresholded second derivatives are used.

  The 2.75 MHz wide range signal depicted in FIG. 4 has a fairly wide bandwidth, but it is not suitable for measuring the range by the method described above. The method requires that the transmitted pulses each have a zero signal lead. However, its purpose can be achieved by modifying the signal so that the sinusoidal waveform between pulses is essentially canceled. In the preferred embodiment, it is done by constructing a waveform very close to the signal on the selected interval between high pulses and then subtracting it from the original signal.

  The technique can be illustrated in FIG. 1 by applying it to the signal. The two black dots shown on the waveform are the end points of section 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:

（１２）

(12)

  An attempt is made to generate a function g (t) that essentially cancels the signal s (t) on this interval but does not cause much harm outside the interval. Equation (11) shows that s (t) is a sinusoidal sin π (2N + 1) Δft modulated by 1 / sin πΔft, so that first, a function h (t) very close to 1 / sin πΔft on interval I. Is then found and formed as a product of g (t).

（１３）

(13)

  h (t) is generated by the following sum.

（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 coefficient a _k is selected to minimize the least square error on interval I.

（１６）

(16)

Solutions are easily obtained by taking partial derivatives J with respect to a _k and by setting them equal to zero. The result is an M + 1 linear equation system.

（１７）

(17)

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

(18)
It 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) on interval I. As shown in the appendix, a suitable choice for the upper limit M for addition in equation (20) is M = 2N + 1. Using this value and the results from the attachment,

(21)

here,
b ₀ = 1− (1/2) a _{2N + 1}
When b _k = 2− (1/2) a _{2 (N−k) +1} 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 sum of 2N + 3 frequencies (including the zero frequency DC term) is 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) requests the 25 carriers (including DC term _{b 0).}

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

  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 a period 1 / Δf, while r (t) has a period 2 / Δf. The first half of each cycle of r (t), which is the entire cycle of s (t), includes the canceled portion of the signal, and the second half of the cycle of r (t) is the large vibration portion. Therefore, cancellation of the preceding wave occurs only in every other period of s (t).

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

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

  5. Immediately after each zero portion of r (t) is the first cycle of the vibrating 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 of s (t) located at approximately the same point. The width of the first half cycle is approximately inversely proportional to NΔf.

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

  (A) Since r (t) is periodic with period 2 / Δf, use repetition of signal r (t). Also, an additional 3 dB processing gain is possible by the method described later.

  (B) Narrowband filtering. Since each of the 2N + 3 carriers is a narrowband signal, the occupied bandwidth of the signal is significantly smaller than that of a wideband signal that spans the entire assigned 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 about 3.7 microseconds or 1,110 meters . This is more than enough to remove the remaining signal from the non-zero part before r (t) due to multipath. The main peak has a value of about 35, and the maximum magnitude in the preceding wave (ie, cancellation) region is about 0.02, which is 65 dB below the main peak. This is desirable to obtain good performance using the TOA measurement threshold technique as described above.

  The use of fewer carriers is depicted in FIG. 6, which illustrates the 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. Since this embodiment has more cycles per unit time, it can be expected that more processing gain can be achieved.

  However, because fewer carriers are used, the main peak amplitude is about 1/3 of the previous magnitude, which tends to eliminate the expected extra processing gain. Also, the length of the zero signal lead wave segment is shorter, approximately 0.8 microseconds or 240 meters. This should still be sufficient to remove the remaining signal from the non-zero part before r (t) due to multipath. Note that the total bandwidth of (2N + 1) Δf = 5.95 MHz is approximately the same as before, and the width of half the main peak cycle 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. In addition, the maximum magnitude in the preceding wave (ie, cancellation) region is now about 75 dB below the main peak, an improvement of 10 dB from the previous example.

Transmission at RF frequency. So far, r (t) has been described as a baseband signal for purposes of brevity. However, it can be converted up to maximum 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 the subscript j ( A frequency of radians / second is used for notational simplicity).

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

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

  As long as the zero signal lead in r (t) has a length sufficiently larger than the largest significant propagation delay, the final baseband signal in equation (20) will still have a zero signal lead. It is important to keep in mind. Of course, when all frequency components (subscript k) on all paths (subscript j) are combined, the baseband signal at the receiver contains the 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 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.

  In FIG. 6, it is assumed that N = 3 and that each of the nine frequency components is continuously transmitted for 1 millisecond. The start and end times for each frequency transmission are known at the receiver, so it can start and end its reception of each frequency component continuously 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 the intended application), a small portion of each received frequency component should be ignored. Yes, the receiver can easily pull it out.

  The entire process of receiving 9 frequency components can be repeated in an additional 9-millisecond block of reception to increase processing gain. With a total reception time of 1 second, there will be about 111 such 9 millisecond blocks available for processing gain. In addition, there will be additional processing gain available in each block from the main peak of 0.009 / (2 / Δf) ≈383.

In general, it is worth noting that signal reconstruction can be performed very efficiently and essentially allows 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 is measured to form a series of stored vectors (phasors) corresponding to that frequency.
2. Average the stored vectors for that frequency.
3. Finally, 2N + 3 vector averages for 2N + 3 frequencies are used to reconstruct one period of the baseband signal with period 2 / Δf, and the reconstruction is used to estimate the signal TOA.

  This method is not limited to 1 millisecond transmission, and the length of the transmission 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.

  Cancellation is obtained on alternating half cycles of r (t) by simply reversing the polarity of the canceling function g (t), and s (if r (t) was previously oscillatory Cancellation between the peaks of t) is possible. However, in order to obtain cancellation between all peaks in s (t), the function g (t) and its polarity reversed need to be applied to the receiver, which is a factor in the receiver Includes weighting.

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

cosω _k t (in the baseband in the transmitter)
cos (ω + ω _k ) t (converted by frequency ω up to the maximum RF)
a _j cos [(ω + ω _k ) (t−τ _j ) + φ _j ] (in the receiver antenna)
a _j cos [ω _k (t−τ _j ) + φ _j + θ] (converted by the frequency −ω up to the baseband)
a _j b _k cos [ω _k (t−τ _j ) + φ _j + θ] (weighted by coefficient bk in baseband)
(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. It should also be noted that coefficient weighting should be performed at the receiver to provide a polarity reversal of g (t) to obtain twice the usable main peak.

  Scaling Δf to center frequency in the channel. In order to meet FCC requirements at VHF or lower frequencies, channelized transmission with constant channel spacing is required. For channeled transmission bands with a constant channel spacing that is small compared to the overall allocated band, as is the case for VHF and lower frequency band (s), a small adjustment to Δf is This allows all transmitted frequencies to be in the center of the channel without substantially changing the performance from the original design value. In the two examples of the baseband signal presented previously, all frequency components are multiple Δf / 2, and therefore the lowest RF transmitted frequency when the channel spacing divides Δf / 2. May be centered within one channel, and every other frequency may be centered on those channels.

  In some radio frequency (RF) -based identifications, in addition to the tracking and locating system performing distance measurement functions, both the master unit and tag unit also perform voice, data, and control communication functions. . Similarly, in the preferred embodiment, both the master unit and the tag perform voice, data, and control communication functions in addition to the distance measurement function.

  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 not the range between voice and / or data and / or control communication, but by its ability to measure distance reliably and accurately. Being outside can be limited.

  In other radio frequency (RF) based identification, tracking, and localization systems, distance measurement functions are separated from voice, data, and control communication functions. In these systems, separate RF transceivers are used to perform voice, data, and control communication functions. The disadvantage of this approach is an increase in system cost, complexity, size, etc.

  In order to avoid the drawbacks mentioned above, in the preferred embodiment, several individual frequency components of a narrowband ranging signal or baseband narrowband ranging signal are used with 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 obtained information reliability is further enhanced by performing “voting” or other signal processing techniques that utilize information redundancy. obtain.

  This method is a “null” phenomenon where RF signals coming from multiple paths are destructively coupled with the DLOS path and each other, thus significantly reducing the received signal strength and the SNR associated therewith. Makes it possible to avoid. Moreover, such a method is a set of frequencies at which the incoming signals from multiple paths are destructively coupled with the DLOS path and each other, and are therefore associated with the received signal strength and with it. It is possible to find frequencies that increase the SNR.

  As previously mentioned, spectral estimation-based super-resolution algorithms generally use the same model, ie, a linear exponential combination of frequencies and their complex amplitudes. This complex amplitude is given by Equation 3 above.

  All of the spectral estimation based super-resolution algorithms require prior knowledge of the number of complex exponents, i.e. the number of multi-passes. 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 delay, which is the case for RF tracking-location applications. This adds another dimension, namely model size estimation, to the spectral estimation process by a super-resolution algorithm.

  In the case of underestimation of the model size, the accuracy of frequency estimation is affected, and if the model size is overestimated, the algorithm has been shown to generate unwanted, eg nonexistent frequencies (non-existing) Patent Document 3). Existing methods of model size estimation, such as AIC (Akaike Information Criterion), MDL (Minimum Description Length), etc., have high sensitivity to correlation between signals (complex exponents). However, this is normal in the case of RF multipath. Further, there is always a residual amount of correlation, for example, after a forward-backward smoothing algorithm is applied.

  The document of Non-Patent Document 3 uses an overestimated model to distinguish the actual frequency (signal) from the unwanted frequency (signal) by estimating these signal powers (amplitudes), then It has been proposed to reject signals with very low power. This method is an improvement over the existing method, but is not guaranteed. The inventors performed the method of Non-Patent Document 3 and performed a simulation for a more complicated case with a larger model size. In some cases, it has been observed that unwanted signals can have an amplitude very close to the actual signal amplitude.

  All of the spectral estimation-based super-resolution algorithms work by dividing the complex amplitude data of the incoming signal into two subspaces: a noise subspace and a 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 achieved using “F” statistics. For example, in the case of the ESPRIT algorithm, the singular value decomposition of the covariance matrix estimation is arranged in ascending order (using forward / backward correlation smoothing). Then, a division is performed, whereby (n + 1) eigenvalues are divided by the nth eigenvalue. This rate is the “F” random variable. The worst case is an “F” random variable with (1,1) degrees of freedom. The 95% confidence interval for the “F” random variable with (1,1) degrees of freedom is 161. Setting that value as a threshold determines the model size. Note also that for the noise subspace, the eigenvalue represents an estimate of the noise power.

  This method of applying the “F” statistic to the eigenvalue rate is a more accurate method of estimating the 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 closely spaced signals (in time) can 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. Since underestimation of the model size reduces the accuracy of frequency estimation, it is advisable to increase the model size by adding a certain number. This number can be determined experimentally and / or from simulation. However, when the signals are not closely spaced, the model size is overestimated.

  In such a case, unnecessary, that is, non-existing 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) has an amplitude very close to the actual signal (s) amplitude. Thus, in addition to amplitude discrimination, a filter can be implemented to improve the possibility of removing unwanted frequencies.

  The frequency estimated by the super-resolution algorithm is an artificial frequency (Equation 2). In fact, these frequencies are individual path delays in a multipath environment. As a result, there should be no negative frequencies and all negative frequencies created 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 a complex amplitude obtained during the measurement using a method different from the super-resolution method.

It can be estimated from the value. Although these methods have lower accuracy, this approach establishes the range used to discriminate delay, ie frequency. For example, signal amplitude

Is close to the maximum, ie avoiding nulls, in Δf intervals

The rate provides a DLOS delay range. The actual DLOS delay can be more than 2 hours or less, but this defines a range that helps to reject unwanted results.

  In an embodiment, the ranging signal performs a round trip. In other words, it moves in both directions, i.e. from the master / reader to the subject / slave and back from the subject / slave to the master / reader.

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

  In the target receiver, received signals (one direction) are as follows.

（２５）

(25)

Here, N is the number of signal paths in the multipath environment, K0 and τ ₀ are the amplitude and time of flight of the DLOS signal, and | K ₀ | = 1, K ₀ > 0, | K _{m ≠ 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 a unidirectional multipath RF channel transfer function in the frequency domain, where A (ω) ≧ 0.

  The target retransmits the received signal.

（２７）

(27)

または、

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

Or

(28)
It is.

（２９） On the other hand, from the 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, the round trip multipath channel has a greater number of paths than the unidirectional channel multipath. Because in addition to τ ₀ ÷ τ _N path delay

This includes a combination of these path delays, for example, 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 signals that are very closely spaced (in time) can also increase, leading to a significant underestimation of the model size. It is therefore desirable to obtain a one-way 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 the round trip phase measurement observation, i.e.

as well as

It 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).

  A mode for carrying out the invention to eliminate this ambiguity will be described 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. An exception is that the phase includes a region close to “null” that can undergo significant changes even at small frequency steps. The “null” phenomenon is when RF signals coming from multiple paths are destructively coupled with the DLOS path and each other, thus significantly reducing the received signal strength and its associated SNR. Keep in mind.

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

(31)
And
Here, B (ω) ≧ 0. The two-way transfer function G (ω) is assumed to be known for all ω in several open frequency intervals (ω ₁ , ω ₂ ). Is it possible to determine the one-way transfer function H (ω) defined on (ω ₁ , ω ₂ ) that generated 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 magnitude in one direction,

(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 an attempt to find the phase of the one-way transfer function from the observation of G (ω), the situation is more difficult to grasp. For each value of ω

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

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

  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 I is a two-way transfer function

Of the frequency ω that does not include zero.

Is a continuous function on I, where β (ω) = 2γ (ω). J (ω) and -J (ω) are then one-way transfer functions that produce G (ω) on I, and there are no others.

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） One solution for a proof one-way transfer function is the function

Since it is differentiable on I, it is continuous on I, where β (ω) = 2α (ω). Since G (ω) ≠ 0 on I, H (ω) and J (ω) are not zero 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. 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, α (ω) −γ (ω) = 0 for all ω∈I, or α (ω) −γ (ω) = π for all ω∈I. In the first case, J (ω) = H (ω) is obtained, and in the second case, J (ω) = − H (ω) is obtained.

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 is

We prove that we get a one-way solution on any open interval I that does not contain any zeros. We function

And γ (ω) satisfying β (ω) = 2γ (ω) is selected so that J (ω) is continuous. It is always possible to do this because it is known that there exists a solution with this characteristic, ie 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

Is a one-way transfer function, and I is an open interval of frequency ω not including zero of H (ω). Then, the phase function α (ω) of H (ω) needs to 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。 Let proof 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 by 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 a circle centered on and in contact with the two lines OA and OB. By assumption, H (ω) is continuous for all ω. Therefore, if ω is close enough to ω ₀ , the complex value H (ω) is in the circle,

It turns out that it is. Since epsilon> 0 is arbitrarily chosen, we, as the phase function alpha (omega) is continuous in omega _0, is α (ω) → α (ω 0) in the omega → omega 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 I is the two-way transfer function

Of the frequency ω that does not include zero.

Is a function on I, where β (ω) = 2γ (ω), and γ (ω) is continuous on I. J (ω) and -J (ω) are then one-way transfer functions that produce G (ω) on I, and there are no others.

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 know that one of the solutions for the one-way transfer function is the function

Where β (ω) = 2α (ω). Since G (ω) ≠ 0 on I, H (ω) and J (ω) are not zero 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) is not discontinuous on I and cannot be converted between these two values. Therefore, α (ω) −γ (ω) = 0 for all ω∈I, or α (ω) −γ (ω) = π for all ω∈I. In the first case, J (ω) = H (ω) is obtained, and in the second case, J (ω) = − H (ω) is obtained.

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 is the transfer function

We show that we get a one-way solution over any open interval I that does not include zeros,

And the value of γ (ω) satisfying β (ω) = 2γα (ω) is selected so that the phase function γ (ω) is continuous. Since it is known that there exists a solution with this characteristic, ie H (ω), this can always be done.

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

Let H (ω) be a one-way function that generates G (ω) on the interval (ω ₁ , ω ₂ ), and that G (ω) has at least one zero on (ω ₁ , ω ₂ ). Assume. The zero of G (ω) separates (ω ₁ , ω ₂ ) into a finite number of open adjacent frequency intervals J ₁ , J ₂ ,..., J _n . On each such interval, the 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 solutions are either H (ω) or −H (ω) over all (ω ₁ , ω ₂ ). To do this, we do not switch from H (ω) to -H (ω) or -H (ω) to H (ω) when moving from one subsection to the next. We need to know how to pair the solutions in two adjacent subintervals.

Illustrate the first of the two open conversion procedure starts with adjacent subintervals J ₁ and J ₂ was. These sub-intervals are adjacent at a frequency ω ₁ that is zero for G (ω) (of course, ω ₁ is not included in any sub-interval). Due to our above assumption on the properties of the one-way transfer function, there must be a minimum positive integer n such that H ⁽ⁿ⁾ (ω ₁ ) ≠ 0, where the superscript (n) is , N-th derivative. Then, whether the limit value of the n th derivative of our one-way solution in J ₁ as omega → omega ₁ from the left, our solution in J ₁ is H (omega) or -H (omega) Accordingly, either H ⁽ⁿ⁾ (ω ₁ ) or -H ⁽ⁿ⁾ (ω ₁ ) is obtained. Similarly, as the omega → omega ₁ from the right extreme value of n derivative of our one-way solution in J ₂ is, that our solution in J _2, -H (ω) or -H (omega) Depending on whether or not, it is either H ⁽ⁿ⁾ (ω ₁ ) or -H ⁽ⁿ⁾ (ω ₁ ). Since H ⁽ⁿ⁾ (ω ₁ ) ≠ 0, the two extreme values are only if and if the solutions at J ₁ and J ₂ are both H (ω) or both -H (ω). , Become equal. If extreme values of the left and right are not equal, it inverts the solution in subinterval J _2. If not, do not flip.

After inverting the solution in sub-interval J ₂ (if necessary), we perform the same procedure for sub-intervals J ₂ and J ₃ and (if necessary) invert the solution in sub-interval J ₃ To do. Continuing in this way, we finally construct a complete solution on the interval (ω ₁ , ω ₂ ).

  It would be desirable that a higher order derivative of H (ω) is not required in the reconstruction procedure. This is because they are difficult to compute accurately in the presence of noise. This is unlikely to happen. 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 not zero. This is because it can be considered.

  In a practical scheme, the two-way transfer function G (ω) is measured at a discontinuous frequency, which is used together to allow a fairly accurate computer calculation of the derivative near zero of G (ω). It needs to be close enough.

  For RF-based distance measurements, it is necessary to eliminate the closely spaced, overlapping, and noisy unknown echoes of ranging signals having a known shape. Assuming that the ranging signal is narrowband, in the frequency domain, this RF phenomenon is described as the sum of several sinusoids for each multipath component and with complex attenuation and propagation delay of the path, respectively ( Modeled).

  Performing the total Fourier transform described above represents this multipath model in the time domain. By exchanging the role of time and frequency variables in this time domain representation, the multipath model becomes a harmonic signal spectrum, where the delayed propagation of the path is converted into a harmonic signal.

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

  Super-resolution spectral estimation uses the eigen structure of the covariance matrix of the baseband ranging signal samples and the eigen properties of the covariance matrix to provide a solution to the underlying estimation of individual frequencies, eg, path delay. One of the eigenstructure properties is that eigenvalues can be combined and consequently divided into orthogonal noise and signal eigenvectors, also known as subspaces. Another intrinsic structural property is a rotation invariant signal subspace property.

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

  The spectral estimation method assumes that the signal is narrowband and the number of harmonic signals is also known, i.e. the size of the signal subspace needs to be known. The size of the signal subspace is called the model size. In general, it cannot be known in detail and can change rapidly when the environment changes, especially indoors. One of the most difficult and difficult problems when applying any subspace decomposition algorithm is the dimension of the signal subspace that can be viewed as the number of frequency components present, which adds the direct path Multipath reflection number. Due to real-world measurement imperfections, there is always an error in model size estimation, which then results in loss of frequency estimation, ie distance accuracy.

  In order to improve the accuracy of the distance measurement, 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 characteristics that further reduce the ambiguity of delay path determination is included.

  Root Music finds individual frequencies that minimize the energy of projection when an observable is projected onto a noise subspace. The ESPRIT algorithm determines individual frequencies from the rotation operator. In addition, in many ways, this operation is Music's conjugate in that when an observable is projected onto the signal subspace, it finds a frequency that maximizes the energy of the projection.

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

  In the case of Music, it is desirable to identify the basic elements of decomposition as “signal eigenvalues” (type 1 error). This minimizes the amount of signal energy projected onto the noise subspace and improves accuracy. In the case of ESPRIT, it is desirable that the reverse is true, i.e., to identify too much 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 in the case of Music is generally somewhat larger than that in the case of ESPRIT.

  Second, in complex signal environments, the model size is estimated with sufficient statistical reliability due to strong reflections and the possibility that the direct path is actually much weaker than some of the multipath reflections. It may be difficult to do. The problem is to process observable data using Music and ESPRIT by estimating the “base” model size for both Music and ESPRIT, and within the model size window defined by the base model size for each Is dealt with by. This results in multiple measurements for each measurement.

  The first feature of the embodiment is the use of the F statistic to estimate the model size (see above). The second feature is the use of different type 1 error probabilities in the F statistic for Music and ESPRIT. This realizes the first type over error between Music and ESPRIT as described above. The third feature is the use of a base model size and window to maximize the probability of detecting a direct path.

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

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

  The method described above may also be used in a wide bandwidth ranging signal location discovery system.

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

(A1)
To get.

が使用される。 Where trigonometric identities

Is used.

to the exclusion of a _0, the coefficient _{a k} is zero in the case of an even number k. This is because, on interval I, the function 1 / sin πΔft we are trying to approximate with h (t) is even about the center of I, but if odd k, k ≠ 0, the basis function sinkπΔft is odd about the center of I and is therefore orthogonal to 1 / sinπΔft on I. Therefore, we can perform k = 2n + 1 permutations, and let M be an odd positive integer. In practice, we assume M = 2N + 1. This choice has been determined experimentally to provide a substantial amount of vibration cancellation within interval I.

（Ａ２）

(A2)

（Ａ３）
を取得する。 Here we perform 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)
As a result.

here,
b ₀ = 1− (1/2) a _{2N + 1}
When b _k = 2− (1/2) a _{2 (N−k) +1} 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

  This embodiment relates to a positioning / positioning method in wireless communications and other wireless networks that substantially eliminates one or more of the disadvantages of the related art. This embodiment advantageously improves the accuracy of tracking and locating 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 (registered trademark), wireless local area networks (WLAN) such as WiFi and UWB, typically wireless metropolitans composed of multiple WLANs. Area network (WMAN), the main example WiMax, wireless wide area network (WAN), eg white space TV band, etc., and mobile device network (MDN) typically used to carry voice and data )including. MDN is typically based on the global mobile communication system (GSM) and personal communication service (PCS) standards. The latest MDN is based on the Long Term Evolution (LTE) standard. These wireless networks are typically base stations, desktops, tablets and laptop computers, handsets, smartphones, actuators, dedicated 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, mobile phone tower triangulation, and Wi-Fi. Some of the methods used to derive this location information include RF fingerprinting, RSSI, and TDOA. Although acceptable to the current E911 requirements, existing location and ranging methods are subject to upcoming E911 requirements and LBS and / or RTLS application requirements, particularly the reliability required to support indoor and urban environments and Not accurate.

  The method described in U.S. Patent No. 6,057,836 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 using 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 location methods.

  The cell ID location technique allows estimation of the location of a user (UE-user equipment) with the accuracy of a specific sector coverage range. 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 an RTT (Round Trip Time) measurement from the eNB. Here, the RTT constitutes the difference between the transmission of the downlink DPCH-dedicated physical channel, (DPDCH) / DPCCH: dedicated physical data channel / dedicated physical control channel) and the start of the corresponding uplink physical frame Keep in mind that In this example, the frame (s) described above function as a ranging signal. The distance from the eNB may be calculated based on information on how much this signal propagates from the eNB to the UE (see FIG. 10).

  In the observed arrival time difference (OTDOA) technique, the arrival times of signals coming from neighboring base stations (eNBs) are calculated. The UE location can be estimated in the handset (UE-based method) or in the network (NT-based UE-assisted method) once signals are received from the three base stations. The signal to be measured is CPICH (Common Pilot Channel). Signal propagation time correlates with locally generated replication. The correlation peak indicates the observed time of propagation of the measured signal. The arrival time difference value between the two base stations determines the hyperbola. At least three reference points are required to define two hyperbolas. The location of the UE is at the intersection of these two hyperbolic curves (see FIG. 11).

  The 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 terminates its transmission and the UEs in the coverage of this cell are distant eNBs. Allows listening to pilots coming from (s). The serving eNB provides inactivity periods in continuous or burst mode. In continuous mode, one inactivity period is inserted every downlink physical frame (10 milliseconds). In the burst mode, the inactivity period occurs pseudo-randomly. Further improvements are obtained with time aligned IPDL (TA-IPDL). Time alignment creates a common inactivity period during which each base station terminates its transmission or transmits a common pilot. Pilot signal measurements are made during periods of inactivity. There are several other techniques that can further enhance the DL OTDOA-IPDL method, such as Cumulative Virtual Blanking, UTDOA (Uplink TDOA), and the like. All of these techniques improve the ability to listen to other (non-serving) eNB (s).

  One significant drawback of OTDOA-based techniques is that base station timing relationships need to be known or measured (synchronized) in order for this method to be feasible. For asynchronous UMTS networks, the 3GPP standard proposes how this timing can be recovered. However, network operators have not implemented such a solution. As a result, alternatives have been proposed that use RTT measurements instead of CPICH signal measurements (see US Pat. No. 6,047,049, 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 arrival times and / or arrival time difference measurements (RTT, CPICH, etc.). The problem with such measurements is that they are severely affected by multipath. This in turn significantly reduces the localization / tracking accuracy of the method / technique described above (see Non-Patent Document 4).

  One multipath mitigation technique uses detection / measurement from the excess of eNB (s) or radio base stations (RBS). The minimum number is 3, but in the case of 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 the UE will hear from this multiple eNB (s) is much lower than from three eNBs (s). This is because, with a large number of RBSs (eNBs), there are 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 reflection (eg multipath), multiple copies of the RF signal with various 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 IDs and OTDOA methods / techniques, including RTT measurements, are of limited bandwidth, DLOS signals and reflected signals are Without proper multipath processing / mitigation, and without this multipath processing, these reflected signals can be estimated to include estimated time difference of arrival (TDOA) and arrival time (including RTT measurements). TOA) Induces errors in the measurement.

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

  In conventional wireless network generations, location accuracy was also affected by the low sampling rate of the frames (signals) used by the location method, ie, RTT, CPCIH, and other signals. The current third and following wireless network generations have fairly high 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 using a wireless network that utilizes OFDM modulation and / or its derivatives. Therefore, the embodiment operates using an LTE network.

  It is also applicable to other wireless networks including WiMax, WiFi, and white space. Other wireless networks that do not use the reference and / or pilot or synchronization signal include the following types of alternative modulation embodiments as described in US Pat. Is dedicated to the ranging signal / ranging signal element, 2) the ranging signal element (Patent Document 3) is embedded in the transmission / reception signal frame (s), and 3) (described in Patent Document 3). One or more of the ranging signal elements) embedded with the data may be utilized.

  These alternative embodiments utilize the multipath mitigation processor and multipath mitigation techniques / algorithms described in U.S. Patent No. 6,057,836 and can be used in full operation modes of simplex, half duplex and full duplex.

  Multiple wireless networks may also utilize preferred and / or alternative embodiments at the same time. As an example, a smartphone may have Bluetooth, WiFi, GSM, and LTE capabilities that have the ability to operate simultaneously on multiple networks. 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 exploit the radio network reference / pilot and / or synchronization signal. Furthermore, the reference / pilot signal / synchronization signal measurement may be combined with RTT (round trip time) measurement or system timing. According to certain embodiments, RF-based tracking and location is implemented on a 3GPP LTE cellular network, but other wireless networks, eg, WiMax, Wi-Fi, LTE, utilizing various signaling techniques, It can also be realized on a sensor network or 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 the embodiment utilizes base station (Node B) / enhanced base station (eNB) hardware / software as well as user equipment (UE), eg, mobile phone or smart phone, hardware / software. A base station generally consists of a transmitter and receiver in a shed or cabinet connected to an antenna by a supply line. These base stations include micro cells, pico cells, macro cells, umbrella cells, mobile phone towers, routers, and femto cells. As a result, there is a slight incremental cost or no incremental cost for the entire UE device and system. At the same time, the localization accuracy is significantly improved.

  The improvement in accuracy results from the multipath mitigation provided by this embodiment and US Pat. Embodiments use multipath mitigation algorithms, network reference / pilot and / or synchronization signals, and network nodes (eNBs). These can be supplemented with RTT (round time trip) measurements. The multipath mitigation algorithm is implemented in the UE and / or base station (eNB) or both the UE and eNB.

  Embodiments provide a multipath mitigation processor / algorithm that allows separation of DLOS and reflected signals even when the DLOS signal is significantly attenuated (less than 10 dB to 20 dB) compared to one or more reflected signals. (See US Pat. No. 6,057,099) is advantageously used. Therefore, the embodiment significantly reduces the estimated ranging signal DLOS time of flight, and consequently errors in TOA, RTT, and DTOA measurements. The proposed multipath mitigation and DLOS differentiation (recognition) method can be used on all RF bands and wireless systems / networks. In addition, it can support various modulation / demodulation techniques including spread spectrum techniques such as DSS (Direct Spread Spectrum) and FH (Frequency Hopping).

  In addition, noise reduction methods can be applied to further improve the accuracy of the method. These noise reduction methods can include, but are not limited to, coherent addition, incoherent addition, adaptive 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, Viterbi algorithm), minimum variance estimation (Kalman filter), and the like.

  In this embodiment, the multipath mitigation processor and multipath mitigation techniques / algorithms do not change the RTT, CPCIH, and other signals and / or frames. This embodiment takes advantage of the radio network reference, pilot, and / or synchronization signal used to obtain the channel response / estimation. The invention uses channel estimation statistics generated by UEs and / or eNBs (see US Pat. Nos. 6,099,086 and 5,836, Iwamatsu et al., APPARATUS FOR ESTIMATING PROPAGATION PATH CHARACTERISTICS).

  An LTE network may use the unique (non-data) reference / pilot and / or synchronous s signal (known signal) transmitted in every downlink and uplink subframe and span the entire cell bandwidth. For the sake of brevity, the reference / pilot and synchronization signals are hereinafter referred to as reference signals. Examples of LTE reference signals are in FIG. 9 (these signals are interspersed between LTE resource elements). From FIG. 2, a reference signal (symbol) is transmitted every six subcarriers. Furthermore, the reference signal (symbol) is shifted in both time and frequency. In total, the reference signal covers every third subcarrier.

  These reference signals are used in initial cell search, downlink signal strength measurement, scheduling, handover, etc. by the UE. A reference signal specific to the UE for channel estimation (response determination) for coherent demodulation is included in the reference signal. In addition to UE-specific reference signals, other reference signals may also be used for channel estimation purposes (see Chen et al., US Pat.

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

  An OFDM symbol consists of a plurality of very closely spaced subcarriers. Inside the OFDM symbol, a time-shifted copy of the current symbol (caused by multipath) results in inter-carrier interference (ICI). In LTE, ICI is addressed (reduced) by determining the multipath channel response and by correcting the channel response at the receiver.

  In LTE, the multipath channel response (estimation) 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), the channel distortion caused by multipath is mitigated by applying amplitude and phase shifts on a subcarrier basis (non-patent literature). 5).

  LTE multipath mitigation is designed to remove ISI and ICI (by inserting a cyclic prefix), but not to separate the DLOS signal from the reflected signal. For example, a time-shifted copy of the current symbol will eventually spread each modulated subcarrier signal, thus causing ICI. Correction of the multipath channel response using the LTE technique described above will eventually reduce the modulated subcarrier signal, but this type of correction will cause the resulting modulated subcarrier signal to be DLOS (inside the OFDM symbol). Do not guarantee that the signal. If the DLOS modulated subcarrier signal is significantly attenuated compared to the delayed reflected signal (s), the resulting output signal is the delayed reflected signal (s) and the DLOS signal is lost. Is called.

  In an LTE compliant receiver, further signal processing includes DFT (Digital Fourier Transform). It is well known that DFT technique (s) can only eliminate (remove) duplication of signal (s) delayed for a time longer than or equal to time inversely proportional to the signal and / or channel bandwidth. is there. The accuracy of this method may be suitable for efficient data transfer, but 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 10 megahertz (1/10 MHz = 100 ns). For better accuracy, the signal and receiver channel bandwidth should be broader, 100 megahertz 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 significantly lower bandwidth than 10 megahertz. Have. As a result, currently utilized methods / techniques (in LTE) result in localization errors in the 100 meter range.

  To overcome the above limitations, embodiments use a unique combination of subspace-resolved high resolution spectral estimation methodology and multimodal cluster analysis implementations. This analysis and the related multipath mitigation methods / techniques and algorithms described in US Pat. No. 6,057,097 allow for reliable and accurate separation of DLOS paths from other reflected signal paths.

  Compared to the methods / techniques used for LTE, in harsh multipath environments, this method / technique and algorithm (US Pat. Through the separation, an accuracy improvement of 20 to 50 times in the distance measurement is achieved.

  The method / technique and algorithm described in US Pat. Thus, LTE reference signals used for channel estimation (response determination) and other reference signals (including pilot and / or synchronization signals) are also used as ranging signals in the method / technique and algorithm 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 calculated (estimated) by the LTE receiver. The response statistic can provide the complex amplitude information required by the method / technique and algorithm described in US Pat.

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

  In this ideal environment, the absolute phase value at the initial (or any) frequency is not important because the derivative is not affected by the phase absolute value.

  In a harsh multipath environment, the phase change with frequency of the received signal is a complex curve (non-linear) and the first derivative is information that can be used for accurate separation of the DLOS path from other reflected signal paths. Do not provide. This is why 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) / technique described in US Pat. As well, the algorithm accurately separates the DLOS path from other reflected signal paths and determines this DLOS path length (time of flight).

  In this phase coherent network / system, no additional measurements are required. In other words, unidirectional ranging can be realized.

  However, if the degree of synchronization (phase coherence) achieved in a given wireless network / system is not sufficiently accurate, in a severe multipath environment, the phase and amplitude change with respect to the frequency of the received signal is 2 It can be very similar to measurements made at two or more different locations (distances). This phenomenon can lead to ambiguity in determining the DLOS distance (time of flight) of the received signal.

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

  However, the amplitude and phase dependence on the frequency computed by the LTE receiver does not include the actual phase value. This is because all amplitude and phase values are computed from the downlink / uplink reference signal, for example with respect to each other. Therefore, the amplitude and phase of the channel response calculated (estimated) by the LTE receiver requires an actual phase value 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, but 1) these signals by the eNB These time stamps that transmit are also known at the receiver (or vice versa), 2) the receiver and eNB clock are well synchronized in time, and / or 3) multi-sided surveying It can be determined by 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, actual phase values at one or more frequencies can be calculated.

  This embodiment provides a multipath mitigation processor, method (s) / technique and algorithm as described in US Pat. 2) Amplitude and phase dependence on the 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 in combination with time stamping measurements to achieve highly accurate DLOS distance determination / location in harsh multipath environments.

  In these cases, the actual phase value (s) is affected by the multipath. However, this does not affect the performance of the method / technique and algorithm 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 a dedicated connection. Therefore, multiple simultaneous measurements are possible when the UE is in a handover state and when the UE periodically collects measurements and reports back to the UE, during which the DPCH frame is transmitted to the UE and different networks ( Exchanged between base stations). Similar to RTT, TOA measurements provide the time of flight (propagation delay) of signals, but TOA measurements cannot be performed simultaneously (Non-Patent Document 4).

  In order to locate the UE on the plane, the DLOS distance needs to be determined from / to at least three eNB (s). At least four DLOS distances to / from four eNB (s) are determined (assuming at least one eNB is not in the same plane) to locate the UE in three-dimensional space Need to be done.

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

  In the 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 such as AOA (angle of arrival) and its combination with other methods may be used for UE location. Can be used.

  The accuracy of the cell ID + RTT tracking-location method is affected by multipath (RTT measurement) and eNB (base station) antenna beamwidth. The antenna beam width of the base station is 33 to 65 degrees. These wide beam widths result in a positioning error of 50-150 meters in the metropolitan area (non-patent document 4). Given the current LTE RTT distance measurement average error of about 100 meters in a harsh multipath environment, the total expected average location error currently utilized by the LTE cell ID + RTT method is about 150 meters.

  One of the embodiments is UE location based on the AOA method, whereby one or more reference signals from the UE are used for UE location purposes. It includes an AOA determination device location for determining the DLOS AOA. The device may be located with the base station and / or installed at another one or more locations independent of the base station location. The coordinates of these locations are known by estimation. No change is required on the UE side.

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

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

  The combination of the embodiment in which accurate DLOS distance measurements are obtained and the embodiment in which accurate DLOS AOA determination can be made significantly improves the cell ID + RTT tracking-location method accuracy by more than 10 times. Another advantage of this approach is that the UE location can be determined at any time using a single tower (does not require placing the UE in soft handover mode). Since the exact location can be obtained using a single tower, there is no need to synchronize multiple cell towers. Another option for determining the DLOS AOA is to use an existing eNB antenna array and eNB equipment. This option may further reduce the cost of implementation of the improved cell ID + RTT method. However, since eNB antennas are not designed for location applications, positioning accuracy can be reduced. Also, the network operator may not attempt to implement the requested changes at the base station (software / hardware).

  In LTE (Evolved Universal Terrestrial Radio Communication Access (E-UTRA), Physical Channel and Modulation, 3GPP TS 36.211 Release 9 Technical Specification), a positioning reference signal (PRS) has been added. These signals are used by the UE for DL-OTDA (downlink OTDOA) positioning. This release 9 also requires that the eNB (s) be synchronized. Therefore, the last obstacle to the OTDOA method is removed (see paragraph 274 above). PRS improves UE audibility in multiple eNB UEs. Note that Release 9 did not specify eNB synchronization accuracy (in some proposals, 100 ns).

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

  The DL-OTDOA method (in Release 9) is described in detail in U.S. Pat. No. 5,849,097 (Method and Apparatus for UE positioning in LTE networks, Chen, at al.). Release 9 DL-OTDOA suffers from multipath. Some of the multipath mitigation can be achieved by increasing the PRS signal bandwidth. However, the price is a longer time between increased scheduling complexity and UE location determination. Moreover, for a network using a limited operating bandwidth, eg 10 MHz, the best possible accuracy is 100 meters, see Chen, Table 1.

  The above numbers are the best possible case. In other cases, particularly when the DLOS signal strength is significantly lower (10-20 dB) compared to the reflected signal (s) strength, the above mentioned localization / ranging errors result (2-4 times). Bring as.

  The embodiments described herein are described in Chen et al. Enables up to 50 times the ranging / positioning accuracy improvement for a given signal bandwidth beyond the performance achieved by the release 9DL-OTDOA and UL-PRS methods. Therefore, applying the method embodiments described herein to Release 9 PRS processing reduces localization errors to 3 meters or better in 95% of all possible cases . In addition, this increase in accuracy reduces scheduling complexity and time between UE location determinations.

  With the embodiments described herein, further improvements for the OTDOA method are possible. For example, ranging for a serving cell can be determined from the signals of other serving cells, thus improving the audibility of neighboring cells and reducing scheduling complexity, including time between UE location determinations.

  Embodiments are also described in Chen et al. (Described in the background art). The accuracy of U-TDOA method and UL-TDOA can be improved up to 50 hours. Applying the embodiment to Chen's UL-TDOA variant reduces localization errors to 3 meters or better in 95% of all possible cases. Moreover, this increased accuracy further reduces scheduling complexity and time between UE location determinations.

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

  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 one-way ranging process be frequency and phase coherent. OFDM-based systems such as 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, for example there is a random phase adder.

  To avoid phase coherence that affects ranging accuracy, multipath processor embodiments calculate different phases between ranging signal (s), eg, reference signal, individual components (subcarriers). To do. This eliminates the random phase term adder.

  Chen et al. As identified above in the discussion of the application of the embodiments described herein, Chen et al. Results in a significant accuracy improvement in indoor environments compared to the performance achieved by See, for example, Chen, et al. According to, DL-OTDOA and / or U-TDOA / UL-TDOA are mainly for outdoor environments, and DL-OTDOA and U-TDOA technologies may not work well indoors (buildings, premises, etc.) There is. Several reasons are noted, including distributed antenna systems (DAS) commonly used indoors, so that each antenna does not have a unique ID (see Chen, # 161-164). ]

  The embodiments described below operate with a wireless network that utilizes OFDM modulation and / or derivatives thereof, and reference / pilot / and / or synchronization signals. Thus, the embodiments described below operate with an LTE network, which also includes other types of modulation, with or without reference / pilot / and / or synchronization signals. As well as other wireless networks.

  The approach described herein is also applicable to other wireless networks, including WiMax, WiFi, and white space. Other wireless networks that do not use reference / pilot and / or synchronization signals include the following types of alternative modulation embodiments as described in US Pat. Use one or more of: 2) the ranging signal element is embedded in the transmit / receive signal frame (s), and 3) the ranging signal element is embedded with data. obtain.

  Embodiments of the multipath mitigation range estimation algorithm described in this specification (also described in Patent Document 10 and Patent Document 11) are composed of multipath reflection plus direct signal path (DLOS). It works by providing a range estimate on the given set.

  The LTE DAS system creates multiple copies of the same signal seen at various time offsets for the mobile receiver (UE). The delay is used to uniquely determine the geometric relationship between the antenna and the mobile receiver. The signal seen by the receiver is similar to that seen by the multipath environment, except for the main “multipath” component result from the sum of the offset signals from multiple DAS antennas.

  The signal set seen by the receiver is in this case identical to the type of signal set embodiment that is designed to utilize, except that the main multipath component is not 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 descriptions). Multipath may exist due to the distributed RF channel (environment), but the main 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 DAS antenna range for the receiver, and provide range data to a location processor (implemented in software). Depending on the geometry of the antenna arrangement, 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). In addition, positioning accuracy can be dramatically reduced by 1) reducing multipath, and 2) in the case of active DAS, eg, from about 50 meters to about 3 meters. Can be significantly improved.

  It is assumed that the position (location) of each antenna of the DAS is known. The signal propagation delay of each antenna (or relative to other antennas) also needs to be determined (known).

  For active DAS systems, the signal propagation delay can be determined automatically using a folding technique, whereby a known signal is sent in a round trip and this round trip time is measured. This folding technique also removes signal propagation delay changes (drift) due to temperature, time, etc.

  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 sets from multiple antennas can be further enhanced by changes to the signal transmission structure in the following two ways. First, the transmission from each antenna is time-multiplexed. The second approach is frequency multiplexing for each of the antennas. Using both enhancements, time and frequency multiplexing simultaneously further improves 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 a particular DAS environment (channel), but so that the multipath caused by the additional delay does not result in ISI (intersymbol interference), It is smaller 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. The carrier phase and amplitude is then estimated using multi-path interference mitigation and multi-edge survey and location consistency algorithms to edit and remove range-based location observables and off-target points. Applied to a multipath processor.

  Another embodiment takes advantage of the fact that the LTE uplink signal also includes a mobile device relative to the base, a reference signal, which also includes a reference subcarrier. In fact, from the full search mode used by the network to allocate frequency bands to uplink devices, the mode in which the reference subcarrier is used to generate a channel impulse response and help demodulate uplink signals, etc. There are two or more modes, including up to these subcarriers. 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, uplink signals are processed by multiple base units (eNBs) using a multipath mitigation process to generate the same range for phase, an observable associated with the range. In this embodiment, a location consistency algorithm is used as established by the multi-sided survey algorithm to edit off-observable points and generate location estimates.

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

  In a DAS (Distributed Antenna System) environment in which multiple antennas transmit the same downlink signal from a microcell, the location matching algorithm (s) is sub-standard (including pilot and / or synchronization) sub-signal (s) sub It is extended to separate the DAS antenna range from the observables generated by the multipath mitigation process from the carrier, and 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 the individual antennas can be solved with high accuracy, so that the path error is the distance between the antennas. Is very small (accuracy of 10 meters or better). All existing techniques / methods cannot provide such accuracy in harsh multipath environments (signals from multiple DAS antennas appear as induced harsh multipath), so existing techniques / methods Cannot successfully utilize the above-mentioned extensions of the location consistency algorithm (s) and this location method / technique in a DAS environment.

  InvisiTrack multipath mitigation method and system for object identification and location discovery described in US Pat. No. 6,057,038 is applied to range, multipath interference mitigation, and process for signal phase mapping, LTE downlink Multi-edge surveying and location consistency using one or more reference signal (s) subcarriers in the uplink, and / or both (downlink and uplink) and 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 has been specified in LTE Release 9, Evolution Universal Terrestrial Radio Access (E-UTRA), Physical Channel and Modulation, 3GPP TS 36.211 Release 9 technical specification. However, it has not been implemented by a wireless operator (carrier). On the other hand, downlink location can be achieved in a current, eg, unmodified, LTE network environment by using existing physical layer measurement operation (s).

  In LTE, the UE and eNB are required to perform physical layer measurements of radio communication features. The measurement definition is specified in 3GPP TS 36.214. These measurements are made periodically and reported to higher layers for various purposes, including intra-frequency and inter-frequency handovers, different inter-radio access technology (inter-RAT) handovers, timing measurements, and RRM ( Used for other purposes in support of (radio communication resource management).

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

  Another example is an RSRQ (reference signal received quality) measurement that provides additional information (RSRQ combines not only signal strength but also interference level).

  The LTE network provides the UE with an eNB neighbor list (relative to the serving eNB). Based on the network knowledge configuration, the (serving) eNode (node) B provides the neighbor eNB identifiers etc. to the UE. The UE then measures the neighbor signal quality that it can receive. The UE reports the result 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 a linear average over the power contribution (in units [W]) of resource elements carrying cell-specific reference signals within the considered measurement frequency bandwidth. The measurement bandwidth used by the UE to determine RSRP is left to the UE implementation with the limitation that the corresponding measurement accuracy requirements need to be met.

  Given the measurement bandwidth accuracy requirements, this bandwidth is quite large, and cell-specific reference signals used in RSRP measurements can be further processed to determine these reference signal subcarrier phases and amplitudes, That phase and amplitude is then applied to the multipath processor for multipath interference mitigation and range-based location observable generation. In addition, other reference signals used in RSRP measurements, such as SSS (secondary synchronization signal) may also be used.

  Then, based on the range observables from more than two cells, location determination can be estimated using multi-sided surveys and location consistency algorithms.

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

  This embodiment can significantly improve the location accuracy of RF fingerprinting because of the ability to locate and characterize individual paths (multi-pass processor), including significantly attenuated DLOS. As a result, the RF fingerprint acquisition decision for location determination can be supplemented with real-time multipath distribution information.

  As described above, location determination requires location reference synchronization in time. In a wireless network, these location references may include so-called small cells (eNBs) as well as access points, macro / mini / pico and femto cells. However, the wireless operator does not implement 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 an FDD (Frequency Division Duplex) network. In the case of LTE TDD (Time Division Duplexing), this time synchronization accuracy is at the limit of +/− 1.5 microseconds. This is equivalent to a location uncertainty of over 400 meters. Although not required, the LTE FDD network is also synchronized, but uses a longer limit (more than 1.5 microseconds).

  Wireless LTE operators are using GPS / GNSS signals to synchronize eNB (s) in frequency and time. The LTE eNB needs to maintain a very accurate carrier frequency, ie 0.05 ppm for macro / minicells and slightly less accurate (0.1-0.25 ppm) for other types of cells. Keep in mind that there are. The GPS / GNSS signal may also be able to improve the accuracy of the requested time synchronization (for location) better than 10 nanoseconds. However, network operators and network equipment manufacturers may use packet transport / Internet / Ethernet® networking, for example, by utilizing NTP (Network Time Protocol) and / or PTP (High Precision Time Protocol), eg, IEEE 1588v2 PTP. In favor of time synchronization, it attempts to reduce the costs associated with GPS / GNSS units.

  IP network-based synchronization has the potential to meet 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 white space.

  The eNB signal is received by a time observation unit (TMO) installed in the operator's eNB facility (FIG. 12). The TMO also includes an external synchronization source input.

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

  The external synchronization source can be from GPS / GNSS and / or Internet / Ethernet networking, such as PTP or NTP.

  Time-stamped processing signals, eg, LTE frame start (which may be other signals, especially in other networks) are also Internet / Ethernet (to the central TMO server that creates, maintains and updates the database of all eNBs ( (Registered trademark) The eNB (cell) location and / or cell ID transmitted via the backhaul is also included.

  The UE and / or eNB (s) involved in the process of ranging and obtaining the location fix quies to the TMO server, which returns the time synchronization offset between the relevant eNB (s). These time synchronization offsets are used by the UE and / or eNB (s) involved in the process of obtaining location fix and adjusting 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. Also good. The TMO server then returns an accurate (coordinated) position (location determination) fix.

  If two or more cell eNB devices are co-located, a single TMO can process and time stamp signals from all eNB (s).

  RTT (Round Time Trip) measurement (ranging) can be used for localization. The disadvantage is that RTT ranging is exposed to multipath that dramatically affects the location accuracy.

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

  At the same time, the multipath mitigation processor, method (s) / technique, and algorithm described in US Pat. ) For example, the multipath channel through which the RTT signal (s) are passing can be identified. This allows correction of the RTT measurement such that the actual DLOS time is determined.

  With a known DLOS time, it is possible to obtain location determination using triangulation and / or similar location methods without the need for location-based synchronization in the eNB or time.

  Despite the TMO and TMO server in place, invisible tracking technology integration requires macro / mini / pico and small cell and / or UE (cell phone) changes. These changes are limited only to SW / FW (software / firmware), but it requires a lot of effort to retrofit the existing infrastructure. Also, in some cases, network operators and / or UE / cell phone manufacturers / suppliers are rebellious against equipment modifications. Note that the 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 with wireless network signals but does not require modification of the wireless network equipment / infrastructure. Therefore, the embodiments described below operate with an LTE network, which is also applicable to other wireless systems / networks, including Wi-Fi.

  In essence, this embodiment creates a parallel wireless location infrastructure that uses wireless network signals to obtain location fixes.

  Similar to the TMO and TMO server, the invisibility tracking location infrastructure collects data from one or more radio network signal acquisition unit (NSAU) and NSAU (s) and analyzes it, And one or more location server units (LSUs) that determine the location and instantly convert it to, for example, a phone / UE ID and location table. The LSU interfaces to the wireless network via the network API.

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

  Coherency timing may be obtained from a GPS clock and / or other stable clock source.

  The NSAU communicates with the LSU via a LAN (Local Area Network), Metro Area Network (MAN), and / or the Internet.

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

  In order to support location services using LTE or other wireless networks, transmitters are required to be clocks and events that are synchronized within tight tolerances. This is usually accomplished by locking in a GPS 1PPS signal. This results in timing synchronization in the local area up to within 3 ns / sigma.

  However, there are many instances where this type of synchronization is not practical. This embodiment provides time offset estimation and tracking of time offsets between downlink transmitters to provide delay compensation values to the location process, so it is as if the transmitters were synchronized clocks and events. The localization process can be processed as if This is achieved by prior knowledge of a transmission antenna and receiver (required for any location service) with a known a priori antenna location. This receiver, called a synchronization unit, collects data from all of the downlink transmitters and its 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 for clock drift in the downlink transmitter. Note that the process of deriving the pseudo range from the received data uses an invisibility tracking multipath mitigation algorithm (described in US Pat. Therefore, synchronization is not affected 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 generated by the synchronized transmitter looks like. Time accuracy is compatible with the best 1-PPS tracking and supports 3 meter location accuracy (1 sigma).

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

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

  An exemplary wireless network location device diagram is depicted in FIG.

Embodiments of fully autonomous systems that utilize LTE signals and are not customer network investments operate in the following modes:
1. Uplink mode uses radio network uplink (UL) signals for location purposes (FIGS. 16 and 17).
2. Downlink mode uses radio network downlink (DL) signals for location purposes (FIGS. 14 and 15).
3. The 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 NSAU (s) antenna locations are selected to minimize GDOP (decrease in geometric accuracy).

  The RF signal of the network from the UE / cell phone device is collected by the NSAU antenna (s) and processed by the NSAU antenna (s), suitable for capturing one or more instances of all signals of interest Producing time-stamped samples of the processed network RF signal during a given time interval.

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

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

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

  Changes / modifications are not required in the radio network infrastructure and / or existing UE / cell phone for UL mode operation.

  In downlink (DL) mode, a UE that can use invisibility tracking is required. Also, the mobile phone FW needs to be modified if the phone is used to obtain location confirmation.

  In some instances, an operator may make a baseband signal available from BBU (s) (baseband unit). In such a case, NSAU (s) can 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 / cell phone ID with one or more radio network signals. Because these signals are processed at the UE / cell phone, or the UE / cell phone periodically generates time-stamped samples of the processed network RF signals and sends them to the LSU, This is because the LSU sends the result (s) back to the UE / cell phone.

  In DL mode, NSAU processes and timestamps the processed RF or baseband (if available) radio network signal. From the captured time-stamped samples, the radio network signal DL frame start associated with the network antenna is determined (acquired) and the difference (offset) between these frame starts is calculated. This operation may be performed by either NSAU or LSU. The frame start offset for the network antenna is stored on the LSU.

  In DL mode, the frame start offset of the network antenna is sent from the LSU to the UE / telephone device if the device processes / determines its own location fix using invisibility tracking techniques. Rather, when the UE / cell phone device periodically sends a processed and time-stamped sample of the RF signal of the network to the LSU, the LSU determines the location of the device and sends the location confirmation data to the device. Send back to.

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

  The bi-directional mode includes the determination of location determination from both UL and DL operations. This allows for further improvements in location accuracy.

  Some enterprise setups are one or more BBUs that supply one or more remote radio communication heads (RRHs), each RRH then supplying the same ID to multiple antennas. Use BBU. In such an environment, depending on the wireless network configuration, the determination of the DL mode frame start offset of the network antenna may not be required. This includes not only a single BBU setup, but also multiple BBUs, whereby each BBU's antenna is assigned to a certain zone and the coverage of adjacent zones is overlapping.

  On the other hand, a configuration in which antennas supplied from multiple BBUs are interleaved in the same zone requires the determination of the DL mode frame start offset of the network antenna.

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

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

However, these consistency algorithms are limited in the number of antennas that emit the same ID. The number of antennas that emit the same ID can be reduced by the following.
1. For a given coverage zone interleaving, antennas supplied from different sectors of a sectorized BBU (BBU can support up to 6 sectors)
2. 2. For a given coverage zone interleaving, antennas fed from different sectors of a sectorized BBU and antennas fed from different BBUs. Add a propagation delay element to each antenna. The cyclic prefix is such that the delay value is large enough to exceed the delay spread in a particular DAS environment (channel), but that the multipath caused by the additional delay does not result in ISI (intersymbol interference). It is selected to be smaller than (CP) length. Adding unique delay IDs for one or more antennas further reduces the number of antennas that emit the same ID.

  In some embodiments, an autonomous system without customer network investment may be proposed. In such embodiments, the system can operate on a band other than the LTE band. For example, the ISM (Industrial Science and Medical) band and / or the white space band may be used in places where LTE services are not available.

  Embodiments may also be integrated with macro / mini / pico / femto station (s) and / or UE (cell phone) equipment. Integration can require customer network investment, which can reduce overhead and dramatically improve TCO (total cost of ownership).

  As described hereinabove, PRS may be used by the UE for time-of-arrival difference (DL-OTDOA) positioning observed on the downlink. Regarding the synchronization of neighboring base stations (eNBs), 3GPP TS36.305 (Stage 2 functional specification of user equipment (UE) positioning in E-UTRAN) defines the transfer timing for the UE, and the timing is a candidate Related to eNode B service of a cell (eg, a neighboring cell). 3GPP TS 36.305 also defines the physical cell ID (PCI) and global cell ID (GCI) of candidate cells for measurement purposes.

  According to 3GPP TS 36.305, this information is delivered from an E-MLC (Enhanced Serving Mobile Location Center) server. Note that TS 36.305 does not specify the timing accuracy described above.

  In addition, 3GPP TS 36.305 specifies that the UE shall return downlink measurements, including reference signal time difference (RSTD) measurements, to E-MLC.

  RSTD is a measurement performed between a pair of eNBs (see TS36.214 Evolutionary Universal Terrestrial Radio Communication Access (E-UTRA), Physical Layer Measurement, Release 9). A measurement is defined as the relative timing difference between the subframe received from neighbor cell j and the corresponding subframe of serving cell i. A positioning reference signal is used to make these measurements. The result is reported back to the location server that calculates the location.

  In certain 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 signal (CRS)), or with both signal types.

  Such a hybrid method provides the advantage of allowing the network operator (s) to dynamically select an operating mode depending on the situation or network parameters. For example, PRS has better audibility than CRS, but can result in up to a 7% reduction in data throughput. On the other hand, CRS signals do not bring any throughput reduction. In addition, the CRS signal is backward 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 a cell or radio node and referred to herein as a “node”) are typically combined into a downlink frame. A receiver for detecting and receiving such signals may detect downlink frames from multiple (two or more) cells or nodes. Each downlink frame includes a plurality of CRS or reference signals. In downlink (DL) frames, these reference signals have a predetermined position in time and frequency, eg, there is a deterministic time offset between the frame start and each CRS in a given frame To do.

  Furthermore, each CRS is modulated using 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 ID (identification) number of the node.

  As a result, by knowing the node ID (s), it is possible to estimate the elapsed location of the frame start time for each frame from each node (cell) in the spectrum of the reference signal. 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, by correlating a received DL baseband signal with a known replica of a code modulated CRS (generated internally by a detector and / or multipath mitigation processor), the various The entire CRS sequence or other reference signal can be found from the node, and this information can be used to find the coarse location frame start of all observable nodes. In certain 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, CRS may also be used as a ranging signal by a multipath mitigation processor. Thus, in addition to finding a coarse frame start, the detector correlation process also uses the codes used to modulate those signals from other signals in the frame (eg, payload, etc.) , CRS can be separated. These separated CRS and associated frame start are then forwarded to the multipath mitigation processor for ranging.

  A similar approach can be used in the 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 in communication with a network is configured to receive a plurality of signals from two or more nodes in communication with the network. A device receiver, wherein a plurality of signals are modulated using a code determined by identification of each of two or more nodes transmitting the plurality of signals, and a plurality of user equipment receivers are based on the identification A reference signal as a ranging signal from each node for tracking and locating a user equipment receiver and one or more wireless network devices, including a detector configured to detect and separate the reference signal from the signal of And a processor configured to use.

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

  In an embodiment, the detector is further configured to estimate the elapsed location by correlating the reference signal with a known replica of such reference signal.

  In an embodiment, 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. Is done.

  In an embodiment, the processor is at least one multipath mitigation processor, and the multipath mitigation processor receives the elapsed location and the separated reference signal to estimate the relative arrival time of the ranging signal from each node. Configured as follows.

  In an embodiment, the processor is at least one multipath mitigation processor.

  In an embodiment, a plurality of signals from each of two or more nodes are in a frame, and the detector is further configured to estimate the elapsed location of the frame start from each node, the detector , Configured to separate the reference signal from any other signal in the frame, the detector further configured to separate the reference signal for each node of the two or more nodes, And the separated reference signal is passed to a multipath mitigation processor, wherein the multipath mitigation processor receives the elapse location and the separated reference signal and compares the ranging signal from each node Configured to estimate arrival time.

  In an embodiment, 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, wherein the device signals transmit one or more device signals. A device that is modulated with a device code determined by a device identification of each wireless network device of the wireless network device, and wherein the node receiver is configured to detect and separate a device reference signal from the device signal based on the device identification A detector, including a detector, is configured to use a device reference signal as a ranging signal from each wireless network device to track and locate one or more wireless network devices.

  In certain embodiments, a user equipment configured to receive a plurality of signals from two or more nodes in communication with a network in a system for tracking and locating one or more wireless network devices in communication with the network. A receiver, wherein a plurality of signals are modulated using a code determined by identification of each node of two or more nodes transmitting the plurality of signals, and a plurality of users based on the identification A processor configured to detect and separate a reference signal from a plurality of signals 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, a plurality of signals from each node of two or more nodes are combined into a frame that includes a reference signal, and the processor is further configured to estimate the elapsed location of the frame start from each node.

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

  In an embodiment, the processor is further configured to estimate the relative arrival time of the ranging signal from each node based on the elapsed location and the separated reference signal.

  In an embodiment, the processor is further configured to separate the reference signal from any other signal 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 two or more nodes are in a frame, and the processor correlates the reference signal with a known replica of the reference signal to initiate a frame start from each node. Further configured to estimate an elapsed location, and further configured to separate the reference signal for each node of the two or more nodes, and for the processor to separate the reference signal from any other signal in the frame And the processor is further configured to estimate a relative arrival time of the ranging signal from each node based on the elapsed location and the separated reference signal.

  In certain embodiments, a detector for tracking and locating one or more wireless network devices in communication with a network is configured to receive a plurality of signals from two or more nodes in communication with the network. A plurality of signals are modulated using a code determined by identification of each of two or more nodes transmitting the plurality of signals, and a reference signal is detected and separated from the plurality of signals based on the identification A detector configured to, 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 two or more nodes are combined into a frame that includes a reference signal, and a detector is further configured to estimate the elapsed location of the frame start from each node.

  In an embodiment, the detector is further configured to estimate the elapsed location by correlating the reference signal with a known replica of such reference signal.

  In an embodiment, 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. Is done.

  In an embodiment, the processor is at least one multipath mitigation processor, and the multipath mitigation processor receives the elapsed location and the separated reference signal to estimate the relative arrival time of the ranging signal from each node. Configured as follows.

  In an embodiment, the processor is at least one multipath mitigation processor.

  In an embodiment, a plurality of signals from each of two or more nodes are in a frame, and the detector is further configured to estimate the elapsed location of the frame start from each node, the detector , Configured to separate the reference signal from any other signal in the frame, the detector further configured to separate the reference signal for each node of the two or more nodes, And the separated reference signal is passed to a multipath mitigation processor, wherein the multipath mitigation processor receives the elapse location and the separated reference signal and compares the ranging signal from each node Configured to estimate arrival time.

  In an 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 using a device code determined by the device identification of each wireless network device of the one or more wireless network devices transmitting the device signal, and the node receiver determines from the device signal based on the device identification A device as a ranging signal from each wireless network device to track and locate the node receiver and one or more wireless network devices, including a device detector configured to detect and separate device reference signals A professional configured to use the reference signal Tsu provided support and, the.

  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 forwarded from UE to E-SMLC according to 3GPP TS 36.305.

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

  An embodiment of UL-TDOA (uplink) is described above in this specification and is shown in FIGS. FIGS. 18 and 19 described herein below provide an alternative example embodiment 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 “listened” by at least three NSAUs, additional NSAUs can be added to improve audibility.

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

  Moreover, the NSAU can be configured to communicate with a location server unit (LSU) over an interface, such as a wired service or a LAN. The LSU can then communicate with the radio or LTE network. The communication can be via a network API, where the LSU can communicate, for example, with an LTE network E-SMLC and can use a wired service, such as a LAN and / or WAN.

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

  In this embodiment, a sounding reference signal (SRS) may be used for location purposes. However, other signals may also be utilized.

  The NSAU can convert the UE uplink transmission signal into digital form, eg, I / Q samples, and can periodically send several converted signals to the LSU using time stamps.

The DAS base station (s) and / or femto / small cell may pass one or all of the following data to the LSU.
1) SRS, I / Q sample, and timestamp,
2) List of supplied UE IDs, and 3) SRS schedule for each UE having UE ID, including SRS scheduling request configuration (Config) information and SRS-UL-config information.

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

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

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

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

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

  In addition, each NSAU may include an input configured for synchronization with an 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 UE location fix.

  As such, the advantages of this embodiment include obtaining a location fix using only a single cell tower (eNB). In addition, this embodiment is configured to operate in a manner similar to that described below in FIG. 18, except that one or more eNBs can be exchanged with DAS base stations and / or femto / small cells. Can be done.

  One method of UE uplink location is the cell identification method (CID). In the basic CID method, the 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. This is a relatively simple method, but 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 the cell diameter 2002 of the serving cell tower 2004 have substantially the same location even though they are not in the same location. 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 includes a number of handsets 2104 that are known to have different locations than other handsets 2000 in other sectors of cell diameter 2002. Are identified.

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. If the UE is connected, RTT or TA may be used for distance 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 the measurement to the eNB (and also under eNB control). Note that LTE Release 9 adds a TA type 2 measurement that relies on 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 transmitted during one PRACH ramping cycle when no response is received from the tracked UE. The LTE type 1TA measurement is equivalent to the RTT measurement as follows.
RTT = TA (type 1) = eNB (Rx−Tx) + UE (Rx−Tx)
Using the knowledge of the eNB coordinates and the serving cell tower antenna height, the UE location may be calculated by the network.

  However, in one dimension, the localization accuracy depends on the sector width and the distance from the serving cell tower, and in the other dimension, the error depends on the TA (RTT) measurement accuracy, so the E-CID localization method. Are still limited. The sector width varies with the 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 even greater 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 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 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 exposed to multipath and topology variations. Nevertheless, an elaborate antenna array can significantly reduce the width 2202 of the sector 2100, which can lead to good location accuracy. Moreover, as illustrated in FIG. 23, if more than one serving cell tower 2300 (eNB base station equipped with a directional antenna array) can be used to make a handset AoA decision, Can be greatly improved. In such cases, accuracy is still exposed to multipath / propagation phenomena.

  Deploying antenna arrays / adaptive antennas across multiple networks over multiple LTE bands requires tremendous effort from a capital, time, maintenance, etc. perspective. As a result, the antenna array / adaptive antenna is not deployed for UE location purposes. Other approaches, such as methods based on signal strength, do not provide significant accuracy improvements. One such signal strength approach is fingerprint acquisition, which is vast and continuously changing (in time) a fingerprint acquisition database, eg, generating large capital and continuously updating, and great accuracy Require that expenses be regenerated without improvement. Moreover, fingerprinting is a UE based technology, whereby the UE location cannot be determined without UE assistance at the UE application level.

  Solutions to other uplink location method limitations include the use of AoA functionality without the need for an antenna array / adaptive antenna. Such embodiments may utilize a TDOA (Time of Arrival Difference) location technique for AoA determination, which may be based on an estimate of the difference in the arrival times of signals from sources at multiple receivers. The individual values of the time difference estimate define 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, the TDOA is equal to the angle between the baseline of the sensor (receiver antenna) and the incident RF energy from the emitter. If the angle between the baseline and true north is known, the bearing line (LOB) and / or AoA can be determined.

  Common location methods using either TDOA or LOB (also known as AoA) are known, but TDOA reference points are too close to each other to make the accuracy of such a technique acceptable. The TDOA location method is not used to determine the LOB. Rather, the LOB is usually determined using a directional antenna and / or a beamforming antenna. However, the super-resolution method described herein makes it possible to dramatically improve accuracy while using TDOA for LOB determination. Furthermore, without using the reference signal processing techniques described herein, “listening”, eg, detecting, a reference signal coming from a UE outside the serving sector, eg, by a non-serving sector and / or antenna. May not be possible. Without using the resolution and processing functions described herein, at least two reference points, eg, two or more sectors and / or antennas) are required, so use TDOA for LOB determination. It may not be possible. Similarly, the UE may not be able to detect a reference signal coming to the UE from outside the serving sector, eg, from a non-serving sector and / or antenna.

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

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 equation defined below can be used to determine the incident RF energy from the emitter, where the time difference in the arrival time 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 two sensors in meters,
Θ is the angle between the sensor baseline and the incident RF wave in degrees;
c is the speed of light.

  Some location techniques are (1) TDOA measurements (multi-sided survey) between two or more serving cells are available, eg, when there is a wide open separation, (2) TDOA measurement is one From only two or more sectors in the above serving cell, eg, from small antenna separation, such LOB / AoA only, (3) combination of methods (2) and (3), and (4) TA measurement and method Available through the use of a combination of (1)-(3), eg, a TDOA location embodiment that includes an improved E-CID.

  As will be described further below, in the case of nearby antennas, the TDOA localization embodiment uses azimuth lines when 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, the 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 the like. 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.

  The serving cell tower 2500 typically consists of a plurality of sectors, as illustrated in FIG. 25, which shows a three-sector (sector A, sector B, and sector C) configuration. The illustrated three sector deployment may include one or more antennas 2502 per sector. A single sector, such as sector A, may be under the control of the UE (handset) because the handset transmission is within sector A's main lobe (the center of the main lobe coincides with the sector azimuth). At the same time, the handset transmission belongs outside the main lobes of sectors B and C, for example in the antenna side lobes. 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 lobe of sector B or sector C. . Nevertheless, as described above and below, through the use of advanced signal processing, sufficient processing gain is obtained on the ranging signal, and these are then used as side lobes of neighboring sectors, eg, sector B and sector C side lobes. And so on. For network-based location purposes, LTE uplink SRS (Sounding Reference Signal) may be used as the ranging signal.

  In other words, the UE uplink reference signal may be in the sidelobe of the neighboring sector (s) antenna, but the processing gain according to the reference signal processing method described herein is 2 (or more). May be sufficient to allow calculation of TDOA between multiple 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 can provide a UE location within an error ellipse of approximately 20 meters x 100 meters.

  Further location error reduction can be achieved when the UE can be heard by more than one LTE tower, which is very likely to use 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 can result in a 30 × 20 meter error ellipse (in the case of two sector cell towers). If each cell tower supports more than two sectors, the error ellipse can be further reduced down to 10-15 meters. If the UE is heard by more than two eNBs (cell towers), accuracy of 5-10 meters can be achieved. In high value areas such as malls, office parks, and similar locations, additional small cells or passive listening devices may be used to generate the necessary coverage.

  As described above, each sector of the 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 composite directional pattern, azimuth, and altitude. The virtual antenna composite directionality and its (main lobe) azimuth and altitude can 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 measurement for each supplied UE is provided to the LSU by each serving sector from each serving cell tower. Assuming that the coordinates of each serving cell tower and each neighboring cell tower field, the azimuth and altitude of each virtual (composite) sector antenna, the number of sectors per tower, and the position of each sector in the cell tower are known, the LSU is , Each UE location for the serving cell tower and / or neighboring cell towers may be determined. All of the information described above can be transmitted over a wired network, such as a LAN, WAN, etc., using one or more standardized or proprietary interfaces. The LSU may also interface with the wireless network infrastructure using a standardized interface and / or a network carrier defined interface / API. The location determination may also be distributed between the network node and the LSU, or may be performed alone at the network node.

  In certain embodiments, location determination may be performed at the UE or may be distributed between the UE and the LSU or network node. In such a case, the UE may communicate wirelessly using standard networking protocols / interfaces. Further, location determination may be performed through a combination of UE, LSU, and / or network nodes, or LSU functionality may be in a SUPL server, E-SMLC server, and / or LCS (Location Service) system. Can be implemented (embedded) and they can then be used instead of LSU.

  The embodiment of the downlink (DL) location method is contrary to the above-described uplink (UL) location embodiment. In a DL embodiment, a sector can be a transmitter having a transmission pattern, azimuth, and altitude that matches the received directionality, azimuth, and altitude of the sector. Unlike the uplink embodiment, in the DL embodiment, the UE typically has a single receive antenna. Therefore, there is no sensor baseline for the UE 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) (multilateral survey) between the sectors, since the sectors of the same cell tower are close to each other, so the hyperbola Can be exchanged for RF energy incident lines or LOB / AoA, as described above with respect to FIG. The accuracy of LOB / AoA can be affected by multipath, noise (SNR), etc., which 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 location can be achieved in a manner similar to UE uplink location, except that the RF wave incident angle cannot be determined from the above equation. Alternatively, multi-sided survey techniques may be used to determine LOB / AoA for each serving cell tower.

  The UE DL location embodiment also utilizes a reference signal. In the case of DL, one approach for such network-based location may be to utilize LTE cell specific reference signals (CRS) as ranging signals. Further, a position reference signal (PRS) introduced in LTE release 9 may be used. Therefore, location can be done using CRS only, PRS only, or both CRS and PRS.

  For UE downlink location embodiments, such as UE uplink location embodiments, 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, a TA measurement for each supplied UE may be provided to the LSU by each serving sector from each serving cell tower (network node). As mentioned above, assuming that the location coordinates of each serving cell tower and each neighboring cell tower, the number of sectors per tower with each sector transmission pattern azimuth and altitude, and the position of each sector in the tower are known, May determine each UE location relative to the serving cell tower and / or neighboring cell towers. In embodiments, location determination may be performed at the UE or distributed between the UE and the LSU or network node. In embodiments, all location determinations can be made at the LSU or network node, or can be distributed between the two.

  The UE communicates / receives measurement results and other information over the air using standard wireless protocols / interfaces. Information exchange between the LSU and the network node (s) may be through a wired network, such as a LAN, WAN, etc., using proprietary and / or one or more standardized interfaces. The LSU may interface with the wireless network infrastructure using a standardized interface and / or a network carrier defined interface / API. The location determination may also be distributed between the network node and the LSU, or may be performed alone at the network node.

  For the UE DL location embodiment described above, antenna port mapping information may also be used to determine the location. The 3GPP TS 36.211 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 included in PDSCH (Physical Downlink Shared Channel). The 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 transmission 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) (multilateral survey) between antennas (assuming the antenna location is 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 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) deployment at an eNB or network node, the receiver (s) may be able to determine the arrival time difference from a given UE. Using antenna knowledge for receiver (s) mapping, eg, MIMO mapping, including antenna location, RF wave incidence (LOB / AoA) for the antenna and hyperbolic (s) for a given eNB antenna ( Multi-side surveying) can also be determined. Similarly, at the UE, the UE receiver (s) can determine the arrival time difference (s) from two or more eNBs or network nodes and MIMO antennas. With knowledge of the location of the eNB antenna and antenna mapping, it is possible to determine the RF wave incidence (LOB / AoA) from the antenna and the hyperbola (s) (multilateral survey) for a given eNB antenna . Depending on where the location determination is made, the antenna mapping information needs to be available to the LSU or UE, or the network node.

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

  In certain aspects, 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 is a geographically distributed cluster of synchronized receivers and / or transmitters within each cluster, precisely in time, eg within 10 ns or better. However, time synchronization between clusters may not be fairly accurate or required at all. Although a precise synchronization time of 10 ns or better is described for a particular embodiment, the predetermined synchronization time required to achieve accurate localization depends on the equipment being utilized. It is important to keep in mind. For example, for some wireless system equipment, if 3m accuracy is required for accurate location determination, the predetermined time may need to be 10ns or better, but other wireless systems In the instrument, the accuracy of the 50m location may be too good. Thus, the predetermined time is based on the desired location accuracy for the wireless system. The disclosed method and system is a significant improvement over existing implementations of tracking and locating DL-OTDOA and U-TDOA techniques, which include geographically distributed stand-alone (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 location is in a network with UEs (handsets) with or without UE assistance or network assistance. It can be estimated in a UE (handset) with (SUPL-based only control plane or user plane) or without network assistance. In DL-OTDOA, once signals from more than two base stations are received, the UE measures the relative timing difference between the signals coming from a pair of base stations and determines the hyperbolic position line (LOP). produce. At least three reference points (base stations that do not belong to a straight line) are required to define two hyperbolas. The UE location (position fix) is at the intersection of these two hyperbolic curves (see FIG. 11). The UE location is related to the (antenna) location of the base station 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 neighbor location management unit (LMU) calculates the relative arrival time of uplink signals coming from the UE (handset), and the location of the UE can be estimated in the network without the assistance of the UE. Therefore, U-TDOA is LMU assisted and E-SMLC (Evolved Serving Mobile Location Center) is server based. Once the relative time-of-arrival values from more than two LMUs are available, the network E-SMLC server creates a hyperbolic location line (LOP) and location (location fix) for the UE (see FIG. 27). . UE location is related to LMU antenna location. In one aspect, unlike DL-OTDOA, in the case of U-TDOA, the eNB's (base station) time synchronization is not required, and only the LMU (s) are highly accurate time synchronization for location purposes. Need. As an example, the LMU is essentially a receiver with computer computing capabilities. As a further example, the LMU receiver utilizes SDR (Software Defined Radio Communication) technology. In further embodiments, the LMU may be a small cell, a macro cell, or a special purpose small cell type device that simply receives.

  Regardless of the implementation, the SRS location correlation for a particular UE allows the UE to be identified and located as prepared by the network. SRS location may be performed at the network level or within a local sector, eg, DAS for buildings, small cells, or a combination of small cells and macro cells that handle a particular area. If the SRS location for the UE is not known a priori, the solution may be able to correlate the UE location through the coverage area. Such correlation indicates a history of where the UE has moved. In some situations, it may be desirable to determine the location of a UE even when the network does not provide an indication of where the SRS is located for a particular UE. The UE location may be correlated with the SRS by determining the UE location or proximity to a known point, thereby correlating the UE with the SRS it is transmitting. Such localization can be accomplished through other location / neighbor resolution, such as Wi-Fi and Bluetooth. The user 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 show only the macro base station. FIG. 27 also depicts that the LMU is located with the base station. Although these depictions are valid choices, the LTE standard does not define where an LMU can be placed as long as the LMU placement meets multi-sided / triangulation requirements.

  In one aspect, common deployments for indoor environments are DAS (Distributed Antenna System) and / or small cells, which are inexpensive base stations that are highly integrated with RF. The LMU (s) can be similarly located in indoor and / or indoor environments, for example, U-TDOA can be used in DAS and / or small cell environments. In another aspect, U-TDOA-based accurate indoor localization uses a combination of indoor-positioned LMUs and externally-positioned macro cells, for example, without the need to deploy DAS and / or small cells. Or may have a reduced number of small cells. Therefore, the LMU can be deployed with or without DAS and / or small cells. In a further aspect, the LMU may be placed in an environment where a cellular signal amplifier / booster is used, with or without DAS and / or small cells.

  LTE Release 11 also contemplates the integration of LMU and eNB into a single unit. However, this is a small, not ready for radio / cellular service provider to meet, especially when the individual small cell eNBs are geographically distributed in indoor and / or other GPS / GNSS rejected environments. Further burden the time synchronization requirements between cells.

  The DAS system is essentially time synchronized to a much higher degree (accuracy) than the geographically distributed macro / mini / small cell / LMU. Using the DL-DTOA solution alleviates the time synchronization problem in a DAS environment, but in a DAS environment, multiple antennas transmit the same downlink signal with the same cell ID (identification number). A single base station handles multiple distributed antennas. As a result, the traditional DL-OTDOA approach fails because there are no identifiable neighboring cells (antennas) that generate signals with different IDs. Nevertheless, when utilizing a multipath mitigation processor and multipath mitigation technique / algorithm as described in US Pat. , They can extend the use of the location integrity algorithm (s) as described in US Pat. The entirety of which is incorporated herein by reference. However, these consistency algorithms are limited in the number of antennas that emit signal (s) with the same ID. One solution is to reduce the number of antennas that emit the same ID, for example, distributing multiple DAS antennas to two or more time-synchronized clusters with different IDs. Such an arrangement increases system costs (increasing the number of base stations) and requires the handset / UE to support the techniques 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 and only the base station software needs to be upgraded to support U-TDOA functionality. Also, multiple LMUs can be integrated with the DAS system. Thus, the use of U-TDOA methods with LMUs has many advantages when utilized indoors, in campus environments, and in other GPS / GNSS severe, geographically limited environments.

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

  In some aspects, time synchronization between multiple distributed base stations and / or small cells / LMUs for many indoor stations and / or small cells and / or for indoor and other GPS / GNSS rejection environments. Or by using an external synchronization source that generates a synchronization signal shared by the LMU. This synchronization signal may be derived from GPS / GNSS, eg 1PPS signal, and / or Internet / Ethernet networking, eg PTP or NTP. The latter is a low cost solution, but it cannot provide the time synchronization accuracy required for accurate location, and the external synchronization signal (s) derived from GPS / GNSS is More accurate, standard deviations up to 20 ns, but requires additional hardware and installation requirements, such as wiring these signals, and is more complex / 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 a higher level of accuracy. Furthermore, the standard deviation of 20 ns is not accurate enough to meet the 3 meter requirement, eg, the standard deviation of about 10 ns.

  To overcome the above limitations, one embodiment uses an LMU device 2800 having 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 RFE (RF Front End) 2806, RF downconverter 2808, and / or 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 are closely time synchronized (eg, standard deviation from about 3 ns to about 10 ns). In another embodiment, antennas 2802 from each LMU signal channel 2804 are geographically distributed (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 attempting close synchronization of several geographically dispersed devices.

  As an example, when two or more multi-channel LMUs (eg, LMU device 2800) are deployed, time synchronization between these LMUs is a low cost and low complexity approach (using external source signals). It can be relaxed so that it can be used to synchronize several distributed multi-channel LMUs. For example, Internet / Ethernet network synchronization can be used, or a common sensor (device) can 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 position lines (LOP) that can be used in determining position fix, but the improvement in time synchronization is this shortage (see description and examples below). 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、

When using multi-sided / triangular surveying, UE positioning accuracy is reduced by two factors: geometric cell tower / small cell / LMU geometrical arrangement (GDOP) And single ranging

Correlation with measurement accuracy (see Non-Patent Document 7). That is,

  The GDOP correlates with the geographical variance of the transmitting antenna (for DL-OTDOA) or receiving antenna (for U-TDOA). In the case of regularly arranged antennas, the two-dimensional GDOP estimate is equal to 2 / √N (H. B. LEE, ACCURACY LIMITATIONS OF HYPERBOLIC MULTILATION SYSTEMS, 1973). Here, in the case of a cellular network, N is the number of “audible” emitters (macro cell tower / small cell / DAS antenna) by the UE (in case of DL-OTDOA), or UE uplink transmission (in case of U-TDOA) ) Is the number of LMU / LMU receive channels. Thus, 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 arranged) single receive channel LMUs are detecting UE uplink transmissions, and these LMUs detect 1 PPS signals (eg, 20 ns standard) It is assumed that they are synchronized by deviation). In this case, N = 8 and there are 7 independent LOPs that can be used for UE location determination. Furthermore, the ranging error standard deviation, σ _R is 3 meters (about 10 ns), and 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 (eg, multi-channel LMU device 2800) with distributed antennas regularly arranged are detecting UE uplink transmissions, each The LMU produces a set of three closely time-synchronized LOPs (eg, a standard deviation of about 3 ns), with N = 4 for three independent LOPs. In this case, two UE location 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 UE position fix errors. One estimate is that the error reduction is proportional to the square root of the number of UE location fixes. In this disclosure, this number is equal to 2, and the final UE location fix error σ _{POS_FINAL} is 2.21 meters, which is obtained as 3.12 / √2.

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

  In another aspect, multiple LMUs may be integrated with the DAS system as illustrated in FIG. As an example, LMU receivers may share the received signal (s) generated by each DAS antenna, eg, share a DAS antenna. The actual distribution of these received signals depends on the DAS implementation, ie active DAS vs. passive DAS. However, the LMU and DAS integrated 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 a calendar to be adapted (correlated). Again, the clustering approach and / or the use of multi-channel LMU (s) is the preferred approach for LMU and DAS integration.

  Also, in a similar manner, the received signal (s) generated by each small cell antenna having an LMU receiver channel can be shared. Here, the time synchronization of the small cells can be relaxed, for example, it is not necessary to satisfy the location requirement, while the LMU / LMU channel requires highly accurate time synchronization. A clustering approach and / or the use of multi-channel LMU (s) is the preferred approach for LMU (s) for such options.

  The integration of LMU and eNB into a single unit has cost advantages over the combination of stand-alone eNB and LMU devices. However, unlike the integrated LMU and eNB receiver, the independent LMU reception 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 independent LMU reception channel is 2 More than one antenna may be supported (and may be time multiplexed with them), eg, more than one small cell can be handled. This can then reduce the number of LMUs (in a small cell / DAS and / or other U-TDOA location environment) and reduce the cost of the system (see also FIG. 28).

  If the wireless / cellular network E-SMLC server lacks the functionality required for DL-OTDOA and / or U-TDOA techniques, this functionality can communicate with the UE and / or LMU. It may be performed by a specific service server and a wireless / cellular network infrastructure and / or location server (see FIGS. 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, for example, as illustrated in FIG. Instead, the listening device can be used to monitor the LMU antenna in the same manner as the WiFi infrastructure. As such, an LMU device and / or a channel antenna serving the LMU may be located with one or more WiFi / listening devices 3500, such as one or more WiFi access points (APs) and the like. As an example, WiFi devices 3500 can be geographically distributed.

  In one embodiment, the WiFi device 3500 may be connected to a power source. The RF analog portion 3502 (eg, circuit) 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 may be connected to an uplink location processor circuit (eg, uplink location processor 2810) via a cable, which may include baseband signal processing. it can. As a further example, such an embodiment facilitates improved signal-to-noise ratio (SNR) because there may be signal amplification between the RF analog portion 3502 and the baseband circuit between the antenna and the interconnect cable. To. In addition, the RF analog portion 3502 can downconvert the received signal (eg, down to baseband), and the baseband signal frequency is somewhat smaller than the received signal at the antenna, so cable requirements Can be relaxed. Such relaxation of cable requirements can result in reduced connection costs and can significantly increase transmission distance.

  It is understood that the ranging signal is not limited to SRS alone, and other reference signals including MIMO, CRS (cell specific reference signal), etc. can be used.

  Thus, although different embodiments of the system and method have been described, it should be apparent to those skilled in the art that certain advantages of the described method and apparatus have been realized. In particular, those skilled in the art will recognize that a system for tracking and locating objects can be assembled using FGPA or ASIC and standard signal processing software / hardware combinations in very small cost increments. It should be. Such systems are useful in various applications, such as human localization in harsh and unfavorable environments, such as indoor or outdoor environments.

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

Claims (37)

A method for determining the location of one or more user equipments (UEs) in a wireless system comprising:
Receiving a reference signal via two or more co-located channels;
Synchronizing the timing of the two or more co-located channels within a standard deviation of a predetermined time or less based on the desired location accuracy for the wireless system;
Calculating the location of at least one UE among the one or more UEs using the received reference signal.   Further comprising utilizing a multipath mitigation processor configured to receive and process the received reference signal, wherein the multipath mitigation processor utilizes high resolution spectral estimation analysis. Reducing the spatial ambiguity associated with the signal, wherein the high resolution spectral estimation estimates a model size for several frequency components of the received reference signal, and a plurality of artificial components of the frequency component Calculating the location of the at least one UE based on a distribution of different frequencies.   The method of claim 2, wherein the high resolution spectral estimation analysis utilizes one or more high resolution spectral estimation algorithms.   The method of claim 3, wherein the one or more high resolution spectral estimation algorithms comprise a matrix bundle algorithm.   The method of claim 1, wherein each of the two or more co-located channels comprises a location management unit card or a small cell.   The method of claim 1, wherein the predetermined time is between about 3 ns and about 10 ns.   The method of claim 1, wherein the received reference signal is an uplink reference signal, a downlink reference signal, a distributed antenna system reference signal, or a combination thereof.   The wireless system includes one or more nodes, each of the one or more nodes includes at least one sector, and the sector of each node is configured to communicate with a location server unit (LSU). The method of claim 1, wherein the utilizing step is performed by the LSU or a combination of the one or more nodes and the LSU.   The wireless system includes one or more nodes, each of the one or more nodes includes at least one sector, and the sector of each node is configured to communicate with a location server unit (LSU). The method of claim 1, wherein the utilizing step is performed by the one or more UEs, the LSU, the one or more nodes, or a combination thereof.   The method of claim 9, wherein the one or more UEs are configured to communicate with the LSU.   The one or more UEs, the LSU, the one or more nodes, or combinations thereof are configured to support multipath mitigation and reference signal processing to calculate the location of each UE. Item 11. The method according to Item 10.   The method of claim 1, wherein the wireless system is configured to include LSU functionality in a network SUPL server, E-SMLC server, LCS (Location Services) system, or a combination thereof. .   The method of claim 1, wherein the wireless system includes an LSU and one or more nodes, wherein the LSU is configured to interface with the one or more nodes and network infrastructure of the wireless system. .   The method of claim 1, wherein the utilizing step comprises utilizing one or more position lines (LOPs).   The method of claim 1, wherein the reference signal is received from geographically distributed antennas. A method for determining the location of one or more user equipments (UEs) in a wireless system comprising:
Receiving a reference signal via a first location management unit having two or more co-located channels;
Synchronizing the timing of the two or more co-located channels within a first standard deviation of a first predetermined time or less based on a desired location accuracy for the wireless system;
Receiving a reference signal via a second location management unit having two or more co-located channels;
Synchronizing the timing of the co-located channels of the second location management unit within a second standard deviation of a second predetermined time or less based on the desired accuracy of the location for the wireless system. When,
The location of at least one UE in the one or more UEs using the received reference signal from the first location management unit and the received reference signal from the second location management unit. Calculating a method.   Further comprising utilizing a multipath mitigation processor configured to receive and process the reference signal from the first location management unit and the second location management unit, the multipath mitigation processor comprising a high resolution Spectral estimation analysis is utilized to reduce spatial ambiguity associated with the received reference signal of the first location management unit and the second location management unit, and the high resolution spectral estimation is Estimating a model size for several frequency components of the received reference signal of the first location management unit and the second location management unit; and distributing a plurality of artificial frequencies of the frequency components 17. The method of claim 16, comprising calculating the location of the at least one UE based on.   The method of claim 17, wherein the high resolution spectral estimation analysis utilizes one or more high resolution spectral estimation algorithms.   The method of claim 18, wherein the one or more high resolution spectral estimation algorithms comprise a matrix bundle algorithm.   The method of claim 16, wherein the first predetermined time and the second predetermined time are between about 3 ns and about 10 ns.   The method of claim 16, wherein the second predetermined time is between about 3 ns and about 10 ns.   The method of claim 16, wherein the received reference signal is an uplink reference signal, a downlink reference signal, a distributed antenna system reference signal, or a combination thereof.   The method of claim 16, wherein the utilizing step comprises utilizing one or more position lines (LOPs).   The method according to claim 16, wherein the first location management unit receives a reference signal from geographically distributed antennas.   The method of claim 16, wherein the second location management unit receives a reference signal from geographically dispersed antennas.   The method of claim 16, wherein the first predetermined time and the second predetermined time are greater than about 10 ns. A method for determining the location of one or more user equipments (UEs) in a wireless system comprising:
Receiving a reference signal via a location management unit having two or more co-located channels that are closely time synchronized with each other;
Computing the location of at least one UE among the one or more UEs using the received reference signal.   28. The method of claim 27, wherein each of the two or more co-located channels comprises a location management unit card or a small cell.   28. The method of claim 27, wherein each of the two or more co-located channels is integrated with the same rack mounting system.   28. The method of claim 27, wherein the co-located channels are synchronized within a standard deviation of a predetermined time based on a desired accuracy of the location for the wireless system.   32. The method of claim 30, wherein the predetermined time is between about 3 ns and about 10 ns.   28. The method of claim 27, wherein the utilizing step comprises utilizing one or more position lines (LOPs).   28. The method of claim 27, wherein the reference signal is received from geographically distributed antennas.   28. The method of claim 27, wherein the reference signal is received from a shared group of antennas communicating with the two or more co-located channels.   28. The method of claim 27, wherein the location management unit or an antenna serving the location management unit is located with a WiFi device.   36. The method of claim 35, wherein the location management unit shares a power source with the WiFi device.   36. The method of claim 35, wherein the antenna serving the location management unit shares a power source with the WiFi device.

Images