Communication apparatus, information processing method, and storage medium

Abstract

To improve estimation accuracy of a position parameter.SOLUTION: A plurality of antennas configured to wirelessly receive a signal from another communication device, a plurality of second signals that are signals corresponding to the first signal and are received by the plurality of antennas when the another communication device transmits a signal including a pulse as the first signal, and a data matrix in which a plurality of correlation calculation results obtained by calculating a correlation between the first signal and the plurality of second signals are arranged are converted into a format including a matrix product of an extended mode matrix and an extended signal matrix; And a control unit configured to estimate a reception time of the second signal based on the extended signal matrix that minimizes a norm of a matrix obtained by weighting the extended signal matrix with a weight smaller than that of the outlier.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a communication device, an information processing method, and a program. [Background technology]

[0002] In recent years, technologies have been developed that allow one device to determine the location of another device based on the results of transmitting and receiving signals between the devices. As an example of a location determination technology, Patent Document 1 below discloses a technology in which a UWB receiver determines the angle of incidence of a radio signal from a UWB transmitter by performing wireless communication using UWB (Ultra-Wide Band). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2015 / 176776 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technique described in Patent Document 1 above leaves room for improvement in the accuracy of estimating position parameters.

[0005] Therefore, the present invention has been made in consideration of the above problems, and an object of the present invention is to provide a mechanism that can improve the estimation accuracy of position parameters. [Means for solving the problem]

[0006] In order to solve the above problem, according to one aspect of the present invention, there is provided a method for wirelessly receiving signals from another communication device, and a method for calculating correlations between a plurality of second signals, which are signals corresponding to the first signals received by the plurality of antennas when the other communication device transmits a signal including a pulse as a first signal, and the first signal at predetermined time intervals, and a data matrix, which is a matrix arranging a plurality of correlation calculation results obtained by calculating correlations between the plurality of second signals and the first signal at the plurality of antennas at the predetermined time intervals, and a data matrix, which represents the correlation calculation results when it is assumed that a signal is received at each of a plurality of set times. and an extended signal matrix, which is a matrix in which a plurality of the correlation calculation results are arranged, and an extended signal vector, which is a vector in which a plurality of elements represent the presence or absence of a signal at the antenna for each set time and the amplitude and phase of the signal, is arranged for a plurality of the correlation calculation results, to a format including a matrix product of the extended mode matrix, which is a matrix consisting of a plurality of elements representing the presence or absence of a signal at the antenna for each set time and the amplitude and phase of the signal, to estimate the extended signal matrix that minimizes a predetermined norm, and to estimate the reception time of the second signal based on the extended signal matrix that minimizes the predetermined norm, wherein the predetermined norm is the norm of a matrix in which the extended signal matrix is ​​weighted with a weight that is smaller for outliers.

[0007] Further, in order to solve the above-mentioned problem, according to another aspect of the present invention, there is provided an information processing method including: calculating a correlation between the first signal and a plurality of second signals, which are signals corresponding to the first signal received by a plurality of antennas when another communication device transmits a signal including a pulse as a first signal, at specified time intervals; converting a data matrix, which is a matrix arranging a plurality of correlation calculation results resulting from calculating the correlation between the plurality of second signals and the first signal at the plurality of antennas at the specified time intervals, into a format including a matrix product of an extended mode matrix, which is a matrix consisting of a plurality of elements that represent the correlation calculation results when it is assumed that a signal is received at each of a plurality of set times, and an extended signal matrix, which is a matrix arranging a plurality of the correlation calculation results, which is a vector consisting of a plurality of elements that represent the presence or absence of a signal at the antenna for each of the set times and the amplitude and phase of the signal; estimating the extended signal matrix that minimizes a predetermined norm; and estimating the reception time of the second signal based on the extended signal matrix that minimizes the predetermined norm, wherein the predetermined norm is the norm of a matrix obtained by weighting the extended signal matrix with a weight that is smaller for outliers.

[0008] Further, in order to solve the above-mentioned problem, according to another aspect of the present invention, a computer is provided which, when another communication device transmits a signal including a pulse as a first signal, calculates a correlation between the first signal and a plurality of second signals which are signals corresponding to the first signal and are received by a plurality of antennas at predetermined times, and calculates a data matrix which is a matrix arranging a plurality of correlation calculation results which are the results of calculating the correlation between the plurality of second signals and the first signal at the plurality of antennas at the predetermined times, and calculates a data matrix which is a matrix consisting of a plurality of elements which represent the correlation calculation results when it is assumed that a signal is received at each of a plurality of set times. A program is provided that converts an extended mode matrix and an extended signal vector, which is a vector consisting of multiple elements that represent the presence or absence of a signal at the antenna for each set time and the amplitude and phase of the signal, into a format that includes a matrix product of the matrix and an extended signal matrix, which is a matrix arranged for multiple correlation calculation results, estimates the extended signal matrix that minimizes a predetermined norm, and functions as a control unit that estimates the reception time of the second signal based on the extended signal matrix that minimizes the predetermined norm, wherein the predetermined norm is the norm of a matrix in which the extended signal matrix is ​​weighted with a weight that is smaller for outliers. [Effects of the Invention]

[0009] As described above, according to the present invention, a mechanism capable of improving the estimation accuracy of position parameters is provided. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating an example of a configuration of a system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram showing an example of the arrangement of a plurality of antennas provided in a vehicle according to the present embodiment. [Figure 3] FIG. 4 is a diagram illustrating an example of position parameters of the portable device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of position parameters of the portable device according to the embodiment. [Figure 5]FIG. 2 is a diagram illustrating an example of a processing block for signal processing in the communication unit according to the present embodiment. [Figure 6] 10 is a graph showing an example of a CIR according to the present embodiment. [Figure 7] FIG. 10 is a sequence diagram showing an example of the flow of a distance measurement process executed in the system according to the present embodiment. [Figure 8] FIG. 10 is a sequence diagram showing an example of the flow of an angle estimation process executed in the system according to the present embodiment. [Figure 9] 10 is a graph for explaining a technical problem of the present embodiment. [Figure 10] 10 is a graph for explaining a technical problem of the present embodiment. [Figure 11] 10 is a graph for explaining a technical problem of the present embodiment. [Figure 12] 10 is a graph for explaining a technical problem of the present embodiment. [Figure 13] FIG. 10 is a diagram for explaining a case where four antennas form a 2×2 planar array. [Figure 14] FIG. 10 is a diagram for explaining the relationship between y(k) and y[i]. [Figure 15] 10 is a flowchart showing an example of the flow of a position parameter estimation process executed by the communication unit according to the present embodiment. [Figure 16] FIG. 10 is a diagram for explaining a case where four antennas form a linear array. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant explanations will be omitted.

[0012] Furthermore, in this specification and drawings, elements having substantially the same functional configuration may be distinguished by adding different letters after the same reference numeral. For example, multiple elements having substantially the same functional configuration may be distinguished as necessary, such as wireless communication units 210A, 210B, and 210C. However, when there is no need to particularly distinguish between multiple elements having substantially the same functional configuration, only the same reference numeral is used. For example, when there is no need to particularly distinguish between wireless communication units 210A, 210B, and 210C, they will simply be referred to as wireless communication unit 210.

[0013] <<1. Configuration Example>> Fig. 1 is a diagram showing an example of the configuration of a system 1 according to an embodiment of the present invention. As shown in Fig. 1, the system 1 according to this embodiment includes a portable device 100 and a communication unit 200. The communication unit 200 in this embodiment is mounted on a vehicle 202. The vehicle 202 is an example of an object of use by a user.

[0014] The present invention involves a communication device on the side of the person to be authenticated and a communication device on the side of the authenticator. In the example shown in Figure 1, portable device 100 is an example of a communication device on the side of the person to be authenticated, and communication unit 200 is an example of a communication device on the side of the authenticator.

[0015] In the system 1, when a user (for example, a driver of the vehicle 202) approaches the vehicle 202 carrying the portable device 100, wireless communication for authentication is performed between the portable device 100 and the communication unit 200 mounted on the vehicle 202. If the authentication is successful, the doors of the vehicle 202 are unlocked and the engine is started, making the vehicle 202 available for use by the user. The system 1 is also called a smart entry system. Each of the components will be described below in order.

[0016] (1) Portable device 100 The portable device 100 is configured as any device carried by a user. Examples of such devices include an electronic key, a smartphone, and a wearable device. As shown in FIG. 1, the portable device 100 includes a wireless communication unit 110, a storage unit 120, and a control unit 130.

[0017] The wireless communication unit 110 has a function of performing wireless communication with the communication unit 200 mounted on the vehicle 202. The wireless communication unit 110 receives wireless signals from the communication unit 200 mounted on the vehicle 202 and transmits wireless signals.

[0018] Wireless communication between the wireless communication unit 110 and the communication unit 200 is realized by signals using, for example, UWB (Ultra-Wide Band). In wireless communication of signals using UWB, if an impulse method is used, the propagation delay time of the radio waves can be measured with high accuracy by using radio waves with an extremely short pulse width of nanoseconds or less, and distance measurement based on the propagation delay time can be performed with high accuracy. Note that the propagation delay time is the time it takes from transmitting to receiving a radio wave. The wireless communication unit 110 is configured as, for example, a communication interface capable of UWB communication.

[0019] Signals using UWB can be transmitted and received as, for example, ranging signals, angle estimation signals, and data signals. The ranging signals are signals transmitted and received in ranging processing, which will be described later. The ranging signals may be configured in a frame format that does not have a payload portion for storing data, or may be configured in a frame format that has a payload portion. The angle estimation signals are signals transmitted and received in angle estimation processing, which will be described later. The angle estimation signals may have the same configuration as the ranging signals. It is preferable that the data signals be configured in a frame format that has a payload portion for storing data.

[0020] Here, the wireless communication unit 110 has at least one antenna 111. The wireless communication unit 110 transmits and receives wireless signals via the at least one antenna 111.

[0021] The storage unit 120 has a function of storing various information for the operation of the portable device 100. For example, the storage unit 120 stores a program for the operation of the portable device 100, as well as an ID (identifier), password, authentication algorithm, and the like for authentication. The storage unit 120 is configured by, for example, a storage medium such as a flash memory, and a processing device that executes recording and reproduction on the storage medium.

[0022] The control unit 130 has a function of executing processing in the portable device 100. As an example, the control unit 130 controls the wireless communication unit 110 to communicate with the communication unit 200 of the vehicle 202. The control unit 130 reads information from the storage unit 120 and writes information to the storage unit 120. The control unit 130 also functions as an authentication control unit that controls authentication processing performed with the communication unit 200 of the vehicle 202. The control unit 130 is configured by electronic circuits such as a CPU (Central Processing Unit) and a microprocessor, for example.

[0023] (2) Communication unit 200 The communication unit 200 is provided in association with the vehicle 202. Here, the communication unit 200 is assumed to be mounted on the vehicle 202, for example, by being installed in the cabin of the vehicle 202 or being built into the vehicle 202 as a communication module. Alternatively, the vehicle 202 and the communication unit 200 may be configured as separate entities, for example, by being installed in a parking lot of the vehicle 202. In this case, the communication unit 200 can wirelessly transmit a control signal to the vehicle 202 based on the result of communication with the portable device 100, thereby remotely controlling the vehicle 202. As shown in FIG. 1 , the communication unit 200 includes a plurality of wireless communication units 210 (210A to 210D), a storage unit 220, and a control unit 230.

[0024] The wireless communication unit 210 has a function of performing wireless communication with the wireless communication unit 110 of the portable device 100. The wireless communication unit 210 receives a wireless signal from the portable device 100 and transmits a wireless signal to the portable device 100. The wireless communication unit 210 is configured as a communication interface capable of UWB communication, for example.

[0025] Here, each wireless communication unit 210 has an antenna 211. Each wireless communication unit 210 transmits and receives wireless signals via the antenna 211.

[0026] The storage unit 220 has a function of storing various information for the operation of the communication unit 200. For example, the storage unit 220 stores a program for the operation of the communication unit 200, an authentication algorithm, etc. The storage unit 220 is configured by, for example, a storage medium such as a flash memory, and a processing device that executes recording and reproduction on the storage medium.

[0027] The control unit 230 has a function of controlling the overall operation of the communication unit 200 and the in-vehicle devices installed in the vehicle 202. As an example, the control unit 230 controls the wireless communication unit 210 to communicate with the portable device 100. The control unit 230 reads information from the storage unit 220 and writes information to the storage unit 220. The control unit 230 also functions as an authentication control unit that controls authentication processing performed between the control unit 230 and the portable device 100. The control unit 230 also functions as a door lock control unit that controls the door locks of the vehicle 202 and locks and unlocks the doors. The control unit 230 also functions as an engine control unit that controls the engine of the vehicle 202 and starts / stops the engine. Note that the power source provided in the vehicle 202 may be a motor or the like in addition to the engine. The control unit 230 is configured as an electronic circuit such as an ECU (Electronic Control Unit).

[0028] <<2. Technical Features>> <2.1. Positional parameters> The communication unit 200 (more specifically, the control unit 230) according to this embodiment performs a location parameter estimation process to estimate location parameters that indicate the location of the portable device 100. Hereinafter, various definitions related to the location parameters will be described with reference to Figs. 2 to 4.

[0029] FIG. 2 is a diagram showing an example of the arrangement of multiple antennas 211 (wireless communication units 210) provided in a vehicle 202 according to this embodiment. As shown in FIG. 2, four antennas 211 (211A-211D) are provided on the ceiling of the vehicle 202. Antenna 211A is provided on the front right side of the vehicle 202. Antenna 211B is provided on the front left side of the vehicle 202. Antenna 211C is provided on the rear right side of the vehicle 202. Antenna 211D is provided on the rear left side of the vehicle 202. The distance between adjacent antennas 211 is set to be equal to or less than half the wavelength λ of an angle estimation signal, which will be described later. A local coordinate system of the communication unit 200 is set as a coordinate system based on the communication unit 200. An example of the local coordinate system of the communication unit 200 is a coordinate system with the center of the four antennas 211 as the origin, the X axis representing the longitudinal direction of the vehicle 202, the Y axis representing the lateral direction of the vehicle 202, and the Z axis representing the vertical direction of the vehicle 202. The X axis is parallel to an axis connecting antenna pairs in the longitudinal direction (for example, antennas 211A and 211C, and 211B and 211D). The Y axis is parallel to an axis connecting antenna pairs in the lateral direction (for example, antennas 211A and 211B, and 211C and 211D).

[0030] The arrangement shape of the four antennas 211 is not limited to a square, but may be a parallelogram, a trapezoid, a rectangle, or any other shape. Of course, the number of antennas 211 is not limited to four.

[0031] FIG. 3 is a diagram showing an example of position parameters of the portable device 100 according to this embodiment. The position parameters may include a distance R between the portable device 100 and the communication unit 200. The distance R shown in FIG. 3 is the distance from the origin of the local coordinate system of the communication unit 200 to the portable device 100. The distance R is estimated based on the results of transmission and reception of a ranging signal, which will be described later, between the portable device 100 and one of the multiple wireless communication units 210. The distance R may also be the distance from one wireless communication unit 210 that transmits and receives a ranging signal, which will be described later, to the portable device 100.

[0032] The position parameters may also include angles of the portable device 100 relative to the communication unit 200, which are composed of an angle α from the X axis to the portable device 100 and an angle β from the Y axis to the portable device 100, as shown in FIG. 3. The angles α and β are angles formed between a line connecting the origin and the portable device 100 in a first predetermined coordinate system and a coordinate axis. For example, the first predetermined coordinate system is a local coordinate system of the communication unit 200. The angle α is an angle formed between the X axis and a line connecting the origin and the portable device 100. The angle β is an angle formed between the Y axis and a line connecting the origin and the portable device 100.

[0033] FIG. 4 is a diagram showing an example of position parameters of the portable device 100 according to this embodiment. The position parameters may include coordinates of the portable device 100 in a second predetermined coordinate system. The coordinate x on the X axis, the coordinate y on the Y axis, and the coordinate z on the Z axis of the portable device 100 shown in FIG. 4 are examples of such coordinates. That is, the second predetermined coordinate system may be a local coordinate system of the communication unit 200. Alternatively, the second predetermined coordinate system may be a global coordinate system.

[0034] <2.2.CIR> (1) CIR calculation process In the location parameter estimation process, the portable device 100 and the communication unit 200 perform communication for estimating location parameters, and calculate a CIR (Channel Impulse Response) during this communication.

[0035] The CIR is a response when an impulse is input to a system. In this embodiment, when a wireless communication unit of one of the portable device 100 and the communication unit 200 (hereinafter also referred to as the transmitting side) transmits a signal including a pulse as a first signal, the CIR is calculated based on a second signal, which is a signal corresponding to the first signal and is received by the wireless communication unit of the other (hereinafter also referred to as the receiving side). It can also be said that the CIR indicates the characteristics of the wireless communication path between the portable device 100 and the communication unit 200. Hereinafter, the first signal will also be referred to as a transmitted signal, and the second signal will also be referred to as a received signal.

[0036] As an example, the CIR may be a correlation calculation result obtained by calculating the correlation between a transmitted signal and a received signal at regular intervals. The correlation here may be sliding correlation, which is a process of calculating the correlation between a transmitted signal and a received signal while shifting their relative positions in the time direction. The CIR includes a correlation value indicating the correlation between the transmitted signal and the received signal as an element for each time interval at a regular time interval. The regular time is, for example, the interval at which the receiving side samples the received signal. Therefore, the elements that make up the CIR are also called sampling points. The correlation value may be a complex number having I and Q components. The correlation value may also be the amplitude or phase of the complex number. The correlation value may also be power, which is the sum of the squares (or the square of the amplitude) of the I and Q components of the complex number.

[0037] The CIR can also be considered as a set whose elements are values ​​at each time (hereinafter also referred to as CIR values). In this case, the CIR is the time-series change of the CIR value. When the CIR is the result of a correlation calculation, the CIR value is a correlation value.

[0038] The portable device 100 and the communication unit 200 acquire the time using a time counter. The time counter counts (typically increments) a value indicating elapsed time (hereinafter also referred to as a count value) at predetermined time intervals (hereinafter also referred to as a count period). The current time is calculated based on the count value counted by the time counter, the count period, and the count start time. The fact that the count periods and count start times are the same between different devices is also referred to as synchronization. On the other hand, the fact that at least one of the count periods and count start times is different between different devices is also referred to as asynchronous or non-synchronous. The portable device 100 and the communication unit 200 may be synchronized or asynchronous. Furthermore, each of the multiple wireless communication units 210 may be synchronized or asynchronous with each other. The specified time for calculating the CIR may be an integer multiple of the count period of the time counter. In the following description, unless otherwise specified, it is assumed that the portable device 100 and each of the multiple wireless communication units 210 are synchronized with each other.

[0039] Hereinafter, the CIR calculation process when the transmitting side is the portable device 100 and the receiving side is the communication unit 200 will be described in detail with reference to FIGS.

[0040] 5 is a diagram showing an example of processing blocks for signal processing in the communication unit 200 according to this embodiment. As shown in FIG. 5, the communication unit 200 includes an oscillator 212, a multiplier 213, a 90-degree phase shifter 214, a multiplier 215, an LPF (Low Pass Filter) 216, an LPF 217, a correlator 218, and an integrator 219.

[0041] Oscillator 212 generates a signal having the same frequency as the frequency of the carrier wave that carries the transmission signal, and outputs the generated signal to multiplier 213 and 90-degree phase shifter 214 .

[0042] Multiplier 213 multiplies the signal received by antenna 211 by the signal output from oscillator 212, and outputs the multiplication result to LPF 216. LPF 216 outputs, of the input signals, signals with frequencies equal to or lower than the frequency of the carrier wave carrying the transmission signal to correlator 218. The signal input to correlator 218 is the I component (i.e., the real part) of the components corresponding to the envelope of the received signal.

[0043] 90-degree phase shifter 214 delays the phase of the input signal by 90 degrees and outputs the delayed signal to multiplier 215. Multiplier 215 multiplies the signal received by antenna 211 by the signal output from 90-degree phase shifter 214, and outputs the multiplication result to LPF 217. LPF 217 outputs, of the input signals, signals with frequencies equal to or lower than the frequency of the carrier wave that carries the transmission signal to correlator 218. The signal input to correlator 218 is the Q component (i.e., the imaginary part) of the components corresponding to the envelope of the received signal.

[0044] Correlator 218 calculates the CIR by taking a sliding correlation between the reference signal and the received signal consisting of I and Q components output from LPF 216 and LPF 217. Note that the reference signal here is the same signal as the transmitted signal before being multiplied by the carrier wave.

[0045] Accumulator 219 accumulates the CIR output from correlator 218 and outputs the result.

[0046] Here, the transmitting side may transmit a signal including a preamble, which includes one or more preamble symbols, as a transmission signal. A preamble is a sequence known between the transmitting and receiving sides. A preamble is typically placed at the beginning of a transmission signal. A preamble symbol is a pulse sequence including one or more pulses. A pulse sequence is a collection of multiple pulses separated in the time direction. The preamble symbols are the target of integration by integration 219. That is, correlator 218 calculates the CIR for each preamble symbol by calculating a sliding correlation between each of the portions corresponding to the multiple preamble symbols included in the received signal and the preamble symbols included in the transmission signal (i.e., the reference signal). Then, integrator 219 integrates the CIR for each preamble symbol for one or more preambles included in the preamble, and outputs the integrated CIR.

[0047] (2) Example of CIR An example of the CIR output from accumulator 219 is shown in Fig. 6. Fig. 6 is a graph showing an example of the CIR according to this embodiment. The CIR shown in Fig. 6 is the CIR when it is assumed that the time when the transmitting side transmits the transmission signal is the counting start time of the time counter. Such a CIR is also called a delay profile. The horizontal axis of this graph is the delay time. The delay time is the time elapsed since the transmitting side transmitted the transmission signal. The vertical axis of this graph is the absolute value of the CIR value (for example, power value). Note that in the following description, CIR refers to the delay profile.

[0048] The shape of the CIR, or more specifically, the shape of the time-series change in the CIR value, is also referred to as the CIR waveform. Typically, in a CIR, a set of elements between zero-crossing points corresponds to one pulse. A zero-crossing point is an element whose value becomes zero. However, this is not always the case in a noisy environment. For example, a set of elements between the intersection points of a reference level and the time-series change in the CIR value can be considered to correspond to one pulse. The CIR shown in FIG. 6 includes a set of elements 21 corresponding to one pulse and a set of elements 22 corresponding to another pulse.

[0049] Set 21 corresponds to, for example, signals (e.g., pulses) that arrive at the receiving end via a fast path. A fast path refers to the shortest path between a transmitter and a receiver. In an environment without obstructions, a fast path refers to a straight path between a transmitter and a receiver. Set 22 corresponds to, for example, signals (e.g., pulses) that arrive at the receiving end via a path other than a fast path. Signals that arrive via multiple paths like this are also called multipath waves.

[0050] (3) Detection of the first arriving wave The receiving side detects, from among the wireless signals received from the transmitting side, signals that satisfy a predetermined detection criterion as signals that have arrived at the receiving side via the fast path.The receiving side then estimates location parameters based on the detected signals.A signal that has been detected as having arrived at the receiving side via the fast path is also referred to as a first arriving wave below.

[0051] The receiving side detects, as the first arriving wave, a signal that satisfies a predetermined detection criterion among the received radio signals. One example of the predetermined detection criterion is that the CIR value (e.g., amplitude or power) exceeds a predetermined threshold for the first time. That is, the receiving side may detect, as the first arriving wave, a signal corresponding to the portion of the CIR whose CIR value first exceeds the predetermined threshold. Hereinafter, the predetermined threshold used to detect the first arriving wave will also be referred to as a fast-path threshold.

[0052] The signal received by the receiving side can be either a direct wave, a delayed wave, or a composite wave. A direct wave is a signal that is received by the receiving side via the shortest path between the transmitter and receiver. In other words, a direct wave is a signal that arrives at the receiving side via a fast path. A delayed wave is a signal that arrives at the receiving side via a path that is not the shortest between the transmitter and receiver, i.e., via a path other than the fast path. A delayed wave is received by the receiving side with a delay relative to the direct wave. A composite wave is a signal that is received by the receiving side in a state where multiple signals that have traveled multiple different paths are combined.

[0053] It should be noted here that the signal detected as the first arriving wave is not necessarily the direct wave. For example, if the direct wave and the delayed wave are received in a state where they cancel each other out, the CIR value of the element corresponding to the direct wave may fall below a predetermined threshold, and the direct wave may not be detected as the first arriving wave. In this case, a delayed wave or a composite wave that arrives later than the direct wave may be detected as the first arriving wave.

[0054] 2.3. Estimation of location parameters (1) Distance estimation The communication unit 200 performs a distance measurement process. The distance measurement process is a process for estimating the distance between the communication unit 200 and the portable device 100. The distance between the communication unit 200 and the portable device 100 is, for example, the distance R shown in FIG. 3. The distance measurement process includes transmitting and receiving a distance measurement signal and calculating the distance R based on the propagation delay time of the distance measurement signal. The propagation delay time is the time it takes for a signal to be received after it is transmitted.

[0055] Here, one of the multiple wireless communication units 210 included in the communication unit 200 transmits and receives a ranging signal. The wireless communication unit 210 that transmits and receives the ranging signal is also referred to as a master hereinafter. The distance R is the distance between the wireless communication unit 210 functioning as the master (more precisely, the antenna 211) and the portable device 100.

[0056] In the ranging process, multiple ranging signals may be transmitted and received between the communication unit 200 and the portable device 100. Of the multiple ranging signals, a ranging signal transmitted from one device to another device is also referred to as a first ranging signal. Next, a ranging signal transmitted from a device that receives the first ranging signal to a device that transmitted the first ranging signal as a response to the first ranging signal is also referred to as a second ranging signal. Next, a ranging signal transmitted from a device that receives the second ranging signal to a device that transmitted the second ranging signal as a response to the second ranging signal is also referred to as a third ranging signal.

[0057] An example of the flow of distance measurement processing will be described below with reference to FIG.

[0058] 7 is a sequence diagram showing an example of the flow of distance measurement processing executed in the system 1 according to this embodiment. This sequence involves the portable device 100 and the communication unit 200. In this sequence, the wireless communication unit 210A functions as the master.

[0059] 7, first, portable device 100 transmits a first ranging signal (step S102). When wireless communication unit 210A receives the first ranging signal, control unit 230 calculates the CIR of the first ranging signal. Thereafter, control unit 230 detects a first incoming wave of the first ranging signal at wireless communication unit 210A based on the calculated CIR (step S104).

[0060] Next, wireless communication unit 210A transmits a second ranging signal in response to the first ranging signal (step S106). Upon receiving the second ranging signal, portable device 100 calculates the CIR of the second ranging signal. Thereafter, portable device 100 detects a first incoming wave of the second ranging signal based on the calculated CIR (step S108).

[0061] Next, portable device 100 transmits a third ranging signal in response to the second ranging signal (step S110). When wireless communication unit 210A receives the third ranging signal, control unit 230 calculates the CIR of the third ranging signal. Thereafter, control unit 230 detects a first incoming wave of the third ranging signal at wireless communication unit 210A based on the calculated CIR (step S112).

[0062] The portable device 100 measures a time INT1 from the transmission time of the first ranging signal to the reception time of the second ranging signal, and a time INT2 from the reception time of the second ranging signal to the transmission time of the third ranging signal. Here, the reception time of the second ranging signal is the reception time of the first arriving wave of the second ranging signal detected in step S108. Then, the portable device 100 transmits a signal including information indicating the times INT1 and INT2 (step S114). The signal is received, for example, by the wireless communication unit 210A.

[0063] The control unit 230 measures a time INT3 from the reception time of the first ranging signal to the transmission time of the second ranging signal, and a time INT4 from the transmission time of the second ranging signal to the reception time of the third ranging signal. Here, the reception time of the first ranging signal is the reception time of the first arriving wave of the first ranging signal detected in step S104. Similarly, the reception time of the third ranging signal is the reception time of the first arriving wave of the third ranging signal detected in step S112.

[0064] Then, the control unit 230 estimates the distance R based on the times INT1, INT2, INT3, and INT4 (step S116). For example, the control unit 230 calculates the propagation delay time τ m Estimate.

[0065]

number

[0066] Thereafter, the control unit 230 calculates the estimated propagation delay time τ m The distance R is estimated by multiplying by the speed of the signal.

[0067] - One of the reasons for the decrease in estimation accuracy The reception times of the ranging signals that are the start and end of times INT1, INT2, INT3, and INT4 are the reception times of the first arriving waves of the ranging signals. As described above, the signal detected as the first arriving wave is not necessarily a direct wave.

[0068] When a delayed wave or a composite wave that arrives later than the direct wave is detected as the first arriving wave, the reception time of the first arriving wave is delayed compared to when the direct wave is detected as the first arriving wave. In this case, the propagation delay time τ m The estimated result of (1) varies from the true value (the estimated result when the direct wave is detected as the first arriving wave). The distance measurement accuracy decreases by the amount of the variation.

[0069] -supplement The receiving side may determine the time when a predetermined detection criterion is satisfied as the reception time of the first arriving wave. That is, the receiving side may determine the time when the power value of the CIR first exceeds a predetermined threshold, or the time when the received power value of the received radio signal first exceeds a predetermined threshold, as the reception time of the first arriving wave. Alternatively, the receiving side may determine the time of the peak of the detected first arriving wave (that is, the time when the power value of the portion of the CIR corresponding to the first arriving wave is highest, or the time when the received power value of the first arriving wave is highest) as the reception time of the first arriving wave.

[0070] (2) Angle estimation The communication unit 200 performs angle estimation processing. The angle estimation processing is processing for estimating angles α and β shown in FIG. 3. The angle acquisition processing includes receiving an angle estimation signal and calculating angles α and β based on the reception result of the angle estimation signal. The angle estimation signal is a signal transmitted and received in the angle estimation processing. An example of the flow of the angle estimation processing will be described below with reference to FIG. 8.

[0071] 8 is a sequence diagram showing an example of the flow of the angle estimation process executed in the system 1 according to this embodiment. The portable device 100 and the communication unit 200 are involved in this sequence.

[0072] As shown in FIG. 8, first, the portable device 100 transmits an angle estimation signal (step S202). Next, when the angle estimation signal is received by each of the wireless communication units 210A to 210D, the control unit 230 calculates the CIR of the angle estimation signal received by each of the wireless communication units 210A to 210D. Thereafter, the control unit 230 detects a first incoming wave of the angle estimation signal for each of the wireless communication units 210A to 210D based on the calculated CIR (steps S204A to S204D). Next, the control unit 230 detects the phase of the detected first incoming wave for each of the wireless communication units 210A to 210D (steps S206A to S206D). Then, the control unit 230 estimates angles α and β based on the phase of the detected first incoming wave for each of the wireless communication units 210A to 210D (step S208).

[0073] Here, the phase of the first arriving wave is the phase of the CIR at the time the first arriving wave is received. Alternatively, the phase of the first arriving wave may be the phase of the received radio signal at the time the first arriving wave is received.

[0074] The process in step S208 will be described in detail below. The phase of the first incoming wave detected by the wireless communication unit 210A is P A The phase of the first arriving wave detected for the wireless communication unit 210B is P B The phase of the first arriving wave detected for the wireless communication unit 210C is P C The phase of the first arriving wave detected for the wireless communication unit 210D is denoted by P D In this case, the antenna array phase difference in the X-axis direction is Pd AC and Pd BD , and the antenna array phase difference Pd in ​​the Y-axis direction BA and Pd DC are expressed by the following equations, respectively.

[0075]

number

[0076] The angles α and β are calculated by the following equation: where λ is the wavelength of the radio wave and d is the distance between the antennas 211.

[0077]

number

[0078] Therefore, the angles calculated based on the respective antenna array phase differences are expressed by the following equations:

[0079]

number

[0080] The control unit 230 determines the calculated angle α AC , α BD , β DC , and β BA For example, the control unit 230 calculates the angles α and β by averaging the angles calculated for each of the two arrays in the X-axis and Y-axis directions, as shown in the following equations.

[0081]

number

[0082] - One of the reasons for the decrease in estimation accuracy As described above, the angles α and β are calculated based on the phase of the first arriving wave. As described above, the signal detected as the first arriving wave is not necessarily a direct wave.

[0083] That is, a delayed wave or a composite wave may be detected as the first arriving wave. Typically, the phases of the delayed wave and the composite wave differ from the phase of the direct wave, and the angle estimation accuracy decreases by the amount of the difference.

[0084] -supplement The angle estimation signal and the ranging signal may be the same. For example, the third ranging signal shown in Fig. 7 may be the same as the angle estimation signal shown in Fig. 8. In this case, the communication unit 200 can calculate the distance R and the angles α and β by receiving one wireless signal that serves as both the angle estimation signal and the second ranging signal.

[0085] (3) Coordinate estimation The control unit 230 performs a coordinate estimation process. The coordinate estimation process is a process for estimating the three-dimensional coordinates (x, y, z) of the portable device 100 shown in Fig. 4. The coordinate estimation process may employ the following first and second calculation methods.

[0086] -First calculation method The first calculation method is a method of calculating coordinates x, y, and z based on the results of distance measurement processing and angle estimation processing. In this case, first, the control unit 230 calculates the coordinates x and y using the following equations.

[0087]

number

[0088] Here, the following relationship holds between the distance R and the coordinates x, y, and z:

[0089]

number

[0090] The control unit 230 uses the above relationship to calculate the coordinate z using the following equation.

[0091]

number

[0092] -Second calculation method The second calculation method is a method of calculating coordinates x, y, and z without estimating angles α and β. First, the following relationship holds based on the above formulas (4), (5), (6), and (7):

[0093]

number

[0094]

number

[0095]

number

[0096]

number

[0097]

number

[0098] By rearranging equation (12) with respect to cos α and substituting it into equation (9), the coordinate x is obtained as follows:

[0099]

number

[0100] By rearranging equation (13) with respect to cos β and substituting it into equation (10), the coordinate y is obtained by the following equation.

[0101]

number

[0102] Then, by substituting the formulas (14) and (15) into the formula (11) and rearranging, the coordinate z is obtained by the following formula.

[0103]

number

[0104] The above has described the process of estimating the coordinates of the portable device 100 in the local coordinate system. By combining the coordinates of the portable device 100 in the local coordinate system and the coordinates of the origin of the local coordinate system in the global coordinate system, it is also possible to estimate the coordinates of the portable device 100 in the global coordinate system.

[0105] - One of the reasons for the decrease in estimation accuracy As described above, coordinates are calculated based on the propagation delay time and phase. These are both estimated based on the first arriving wave. Therefore, for the same reasons as in the ranging process and angle estimation process, the accuracy of coordinate estimation may be reduced.

[0106] (4) Estimation of the area of ​​existence The position parameters may include an area in which the portable device 100 is present, among a plurality of predefined areas. As one example, when an area is defined by a distance from the communication unit 200, the control unit 230 estimates the area in which the portable device 100 is present, based on the distance R estimated by the distance measurement process. As another example, when an area is defined by an angle from the communication unit 200, the control unit 230 estimates the area in which the portable device 100 is present, based on the angles α and β estimated by the angle estimation process. As another example, when an area is defined by three-dimensional coordinates, the control unit 230 estimates the area in which the portable device 100 is present, based on the coordinates (x, y, z) estimated by the coordinate estimation process.

[0107] Additionally, as a process specific to the vehicle 202, the control unit 230 may estimate the area where the portable device 100 is located from among a plurality of areas including the interior and exterior of the vehicle 202. This makes it possible to provide a more detailed service, such as providing different services depending on whether the user is inside or outside the vehicle. Additionally, the control unit 230 may specify the area where the portable device 100 is located from among a peripheral area, which is an area within a predetermined distance from the vehicle 202, and a distant area, which is an area at a predetermined distance or more from the vehicle 202.

[0108] (5) Use of location parameter estimation results The estimation result of the position parameter can be used, for example, for authenticating the portable device 100. For example, when the portable device 100 is located in an area close to the communication unit 200 on the driver's seat side, the control unit 230 determines that the authentication is successful and unlocks the door.

[0109] <<3.Technical issues>> The technical problem of this embodiment will be explained with reference to Figs. 9 to 12. Figs. 9 to 12 are graphs for explaining the technical problem of this embodiment. The horizontal axis is the chip length indicating the delay time, and the vertical axis is the absolute value of the CIR value (for example, power value). The chip length is the time width per pulse. For example, when a pulse is generated with a bandwidth of 500 MHz, the chip length is a pulse width of approximately 2 ns.

[0110] In Figure 9, the delay time is 1T C The signal arrives via the fast path at C 9 shows the CIR when a signal arrives via a path other than the fast path. C and 3T C Therefore, the delay time is 2T. C It can be seen that the CIR waveform is sufficient to separate two distant multipath waves.

[0111] In Figure 10, the delay time is 1T CThe signal arrives via the fast path at C The CIR is shown for when a signal arrives via a route other than the fast path. C The first wave signal arrives at and the delay time is 2T C 10, the delay time is 1T. C While the CIR waveform has a peak at the delay time 2T C Furthermore, there is no peak in the CIR waveform at the delay time of 1T. C The signal arrives at the time delay 2T. C The signal arriving at is synthesized in phase with the signal arriving at the time, and appears as a single waveform. C It is clear that it is difficult to separate two distant multipath waves using a CIR waveform.

[0112] In Figure 11, the delay time is 1.2T. C The signal arrives via fast path at C and 3.6T C The CIR is shown for signals arriving via routes other than the fast path. Note that the delay time is 1.2T. C The first wave signal arrives at 1.7T. C 11, the delay time is 1.2T. C and 3.6T C On the other hand, the CIR waveform peaks at a delay time of 2.2T. C A second peak appears around this point. This is the true delay time of 1.7T. C Therefore, the delay time is 0.5T. C It is clear that it is difficult to separate two distant multipath waves using a CIR waveform.

[0113] As shown in Figures 10 and 11, if the difference in delay time between the arrival of two multipath waves at the receiving end is short, the delay time at which the peak appears in the CIR waveform may deviate from the actual delay time. As a result, the delay time detected as the reception time of the first arriving wave may deviate from the actual delay time. In this case, the deviation will reduce the ranging accuracy.

[0114] In Figure 12, the delay time is 1T C The signal arrives via fast path at C 2 shows a CIR waveform 23 when a signal arrives via a path other than the fast path. The CIR waveform 21 has a delay time of 1T C The CIR waveform 22 is a CIR waveform when a signal that has passed through the fast path is received alone at the time of the delay time 1.5T. C This is the CIR waveform when a signal that has passed through a route other than the fast path is received alone. C The first wave signal arrives at and the delay time is 2T C The second signal arriving at is 90 degrees out of phase with the first signal.

[0115] When the difference in delay time between the arrival of two multipath waves at the receiving end is short, a delayed wave or a composite wave may be detected as the first arriving wave. In the example shown in Figure 12, the composite wave is detected as the first arriving wave. Typically, the phases of the delayed wave and the composite wave differ from the phase of the direct wave, and the angle estimation accuracy decreases accordingly.

[0116] 12, when a composite wave of a direct wave and a delayed wave is detected as the first arriving wave, the phase fluctuates significantly at sampling point 31 near the peak due to the composite of delayed waves. Therefore, if angle estimation is performed based on the phase at sampling point 31, the estimation accuracy will be reduced.

[0117] On the other hand, at low-power sampling points before the peak, such as sampling point 32, the influence of delayed waves is reduced, resulting in smaller phase fluctuations. However, the power value decreases in exchange for the reduced influence of delayed waves, which increases the influence of noise and reduces the estimation accuracy accordingly.

[0118] Therefore, it is desirable to be able to separate multipath waves with a resolution higher than that of CIR.

[0119] <<4. Technical Features>> 4.1. Detection of the first arriving wave The portable device 100 and the communication unit 200 detect the first incoming wave through the process described in detail below. As an example, the case where the subject that detects the first incoming wave is the communication unit 200 will be described below. The process described below may be executed by the portable device 100.

[0120] (1) Delay profile formulation First, we formulate the delay profile (i.e., CIR) in the PN (Pseudo-Noise) correlation method. The PN correlation method is a technique that calculates the CIR by transmitting a signal consisting of a random sequence, such as a PN sequence signal shared by the transmitter and receiver, and taking the sliding correlation between the transmitted signal and the received signal. Note that a PN sequence signal is a signal in which 1s and 0s are arranged almost randomly.

[0121] In the following, it is assumed that a PN sequence signal u(t) of unit amplitude is transmitted as a transmission signal (for example, a preamble symbol of a ranging signal and an angle estimation signal). The unit amplitude is a specified amplitude that is known between a transmitter and a receiver.

[0122] In the following, it is assumed that the receiving antenna receives L multipath waves as signals corresponding to the transmitted signal from the transmitting side. Multipath waves are signals that are received by the receiving side via multiple paths. In other words, when the transmitting side transmits one signal, L signals that have traveled multiple paths are received by the receiving side.

[0123] In this case, the received signal x(t) is expressed by the following equation:

[0124]

number

[0125] where t is the time. i is the complex response value of the ith multipath wave. T 0i is the propagation delay time of the ith multipath wave. f is the frequency of the carrier wave of the transmitted signal. v(t) is the internal noise. Internal noise is noise generated within the circuitry on the receiver side.

[0126] For example, in the PN correlation method, the correlation between the received signal x(t) and a known transmitted signal u(t) is calculated on the receiver side while shifting the time of the transmitted signal u(t), as shown in the following equation.

[0127]

number

[0128] In addition, u * () is the complex conjugate of u().

[0129] z(τ) is also called a delay profile. 2 is also referred to as the power delay profile, and τ is the delay time.

[0130] The delay profile when L-wave multipath waves are received is expressed by the following equation:

[0131]

number

[0132] Here, r(τ) is the autocorrelation function of the PN sequence signal. The autocorrelation function is a function that takes the correlation between a signal and the signal itself. r(τ) is given by the following equation.

[0133]

number

[0134] Furthermore, n(τ) is the internal noise component, which is given by the following equation:

[0135]

number

[0136] (2) Sparse reconstruction The number of samples of the received signal is M (where M>L). The received signal is divided into M discrete delay times τ1, τ2, ..., τ M The discrete delay time is a delay time expressed as a discrete value. z(τ) is a delay profile calculated based on the received signal sampled at the discrete delay time τ. The data vector z consisting of M delay profiles is expressed by the following equation. However, this equation applies when the receiving side receives only one preamble symbol.

[0137]

number

[0138] When a multipath wave of an L wave is received, the data vector z is expressed as follows:

[0139]

number

[0140]

number

[0141]

number

[0142] Note that r(τ) is called a mode vector.

[0143] Furthermore, when the data vector z is expressed in matrix notation, it is expressed as follows:

[0144]

number

[0145]

number

[0146]

number

[0147] Here, A0 is also called the modal matrix.

[0148] S0 is also called the signal vector.

[0149] In sparse reconstruction, the data vector z is transformed into a form involving a matrix product of A and s.

[0150]

number

[0151]

number

[0152]

number

[0153] T1, T2, …, T N represents the N delay times to be searched: T1, T2, ..., T Nis also referred to as a delay time bin. The delay time bin is an example of a set time. Note that N >> L.

[0154] Here, A is also referred to as an extended mode matrix. The extended mode matrix is a matrix consisting of a plurality of elements representing a delay profile when it is assumed that signals are received at each of a plurality of delay time bins. For example, r(T1), which is an element of the extended mode matrix A, is the delay profile of the signal when it is assumed that the signal is received at time T1.

[0155] Also, s is also referred to as an extended signal vector. The extended signal vector is a vector consisting of a plurality of elements representing the presence or absence of signals for each delay time bin, as well as the amplitude and phase of the signal.

[0156] (3) Estimation of propagation delay time based on the extended signal vector According to sparse reconstruction, the delay profile z is modeled in the form of As + n. Therefore, it is possible to obtain the extended signal vector s by solving an underdetermined problem where the number of unknowns is N and the condition number is M (M < N). The control unit 230 estimates the reception time of the first arriving wave based on the delay time bins corresponding to the plurality of elements in the extended signal vector s.

[0157] Here, non-zero elements in the extended signal vector indicate that a signal exists in the delay time bin corresponding to the non-zero element. On the other hand, zero elements in the extended signal vector indicate that no signal exists in the delay time bin corresponding to the zero element. Therefore, the control unit 230 estimates the delay time bin corresponding to the non-zero element among the delay time bins corresponding to the plurality of elements in the extended signal vector s as the reception time of the first arriving wave.

[0158] In this case, the control unit 230 estimates a sparse solution of the extended signal vector s, and estimates the delay time bin corresponding to the non-zero elements of the estimated sparse solution as the reception time of the first arriving wave. A sparse solution is a vector in which only a predetermined number of elements are non-zero. The predetermined number is the number of pulses contained in the received signal, which corresponds to one pulse contained in the transmitted signal. In other words, when L multipath waves are received, a sparse solution is a vector in which only L elements are non-zero and the other elements are zero. For example, s=[s1,s2,...,s N ] is non-zero, it is determined that a signal is received at delay time T2.

[0159] In particular, the control unit 230 estimates the earliest delay time bin among the delay time bins corresponding to non-zero elements included in the extended signal vector s as the reception time of the first arriving wave. For example, s=[s1, s2, ..., s N If s2, s4, and s6 are non-zero, it is determined that a signal via the fast path is received at delay time T2, and that signals via a route other than the fast path are received at delay times T4 and T6.

[0160] The resolution of the signal obtained by the sparsely reconstructed model is determined by the size of N (i.e., the number of elements of the extended signal vector s) when modeling in the sparse reconstruction. Therefore, by increasing the number of N when performing the sparse reconstruction, it becomes possible to separate multipath waves with a finer resolution than CIR. Therefore, in this embodiment, the number of delay time bins N is made larger than the number of samples M of the received signal. In other words, in this embodiment, N delay time bins T1, T2, ..., T N The time interval is made up of M discrete delay times τ1, τ2, …, τ M This configuration makes it possible to separate multipath waves with a resolution finer than the sampling interval of the received signal. As a result, it becomes possible to determine the reception time of the first arriving wave with a resolution finer than the CIR.

[0161] (4) Compressed sensing algorithm The control unit 230 estimates an extended signal vector s that is a sparse solution using a compressed sensing algorithm. The compressed sensing algorithm is an algorithm that assumes that an unknown vector is a sparse vector and estimates the unknown vector based on linear observation of the unknown vector. In this embodiment, the extended signal vector s is an example of an unknown vector. Linear observation is obtaining a result of multiplying the unknown vector by a coefficient. In this embodiment, the extended mode matrix A is an example of a coefficient. The delay profile z is an example of linear observation.

[0162] Examples of compressed sensing algorithms include FOCUSS (Focal Underdetermined System Solver), ISTA (Iterative Shrinkage Thresholding Algorithm), and FISTA (Fast ISTA). In particular, FOCUSS is an algorithm that assumes an initial value for an unknown vector and iteratively estimates the unknown vector using a generalized inverse matrix and a weighting matrix. By using a generalized inverse matrix and a weighting matrix, FOCUSS can accurately estimate the unknown vector with a small number of iterations. The basic principles of FOCUSS are explained in detail in the first non-patent document, "Irina F. Gorodnitsky, Member, IEEE, and Bhaskar D. Rao, "Sparse Signal Reconstruction from Limited Data Using FOCUSS: A Re-weighted Minimum Norm Algorithm," IEEE Transactions on Signal Processing, Vol. 45, No. 3, March 1997."

[0163] Another example of a compressed sensing algorithm is M-FOCUSS (FOCUSS with multiple measurement vectors), which is an extension of the above-mentioned FOCUSS. M-FOCUSS is an algorithm that applies FOCUSS in parallel to multiple unknown vectors. The basic principles of M-FOCUSS are explained in detail in the second non-patent document, "Shane F. Cotter, et al; "Sparse Solutions to Linear Inverse Problems With Multiple Measurement Vectors," IEEE Transactions on Signal Processing, vol. 53, No. 7, July 2005, pp. 2477-2488."

[0164] The control unit 230 according to this embodiment uses M-FOCUSS to estimate the reception time of the first arriving wave. To do this, first, the control unit 230 performs sparse reconstruction to enable the use of M-FOCUSS. More specifically, the control unit 230 converts a data matrix obtained by expanding a data vector z for multiple wireless communication units 210 into a matrix product format of an expanded mode matrix and an expanded signal matrix obtained by expanding an expanded signal vector s for multiple wireless communication units 210. Then, the control unit 230 uses M-FOCUSS to estimate an expanded signal matrix that satisfies a predetermined condition, and estimates the reception time of the first arriving wave based on the estimation result.

[0165] -Redefinition of the formula for sparse reconstruction In the above, a formulation was given for the case where the CIR is calculated and sparse reconstruction is performed for a received signal received by one wireless communication unit 210 (i.e., one antenna 211). Below, a formulation is given for multiple received signals received by multiple wireless communication units 210 (i.e., multiple antennas 211).

[0166] When the portable device 100 transmits a transmission signal, the control unit 230 calculates the CIR for each of the plurality of wireless communication units 210 by calculating the correlation between the received signal received by each of the plurality of wireless communication units 210 and the transmission signal at regular intervals from the timing set for each of the plurality of wireless communication units 210. The timing set for each of the plurality of wireless communication units 210 refers to the count start time of a time counter for each of the plurality of wireless communication units 210. In the following description, it is assumed that the count start time for each of the plurality of wireless communication units 210 is the same. In other words, it is assumed that each of the plurality of wireless communication units 210 is synchronized with each other. Of course, each of the plurality of wireless communication units 210 may be asynchronous.

[0167] The number of wireless communication units 210 (i.e., the number of antennas 211) is K, and an index indicating an individual antenna 211 is k. Z is the CIR obtained by correlating the received signal received by the k-th antenna with the transmitted signal. k (τ) is expressed by the following equation:

[0168]

number

[0169] where x k (t) is the signal received by the k-th antenna.

[0170] The CIR at the kth antenna is discretized as a data vector z (k) is expressed by the following equation:

[0171]

number

[0172] where A s is a modal matrix in which all the L-wave mode vectors are arranged in a column. s is expressed by the following equation:

[0173]

number

[0174]

number

[0175] Also, s s is a signal vector at a reference antenna (hereinafter also referred to as a reference antenna) among the K antennas. s is expressed by the following equation:

[0176]

number

[0177] Also, B k is a diagonal matrix that indicates the phase difference of the kth antenna relative to the reference antenna. k is expressed by the following equation:

[0178]

number

[0179] where r kL is the phase difference that occurs depending on the angle of arrival when the k-th antenna receives the L-th pulse. The phase difference here is the phase delay with respect to the reference antenna. As an example, when K=4 and four antennas 211 form a 2 × 2 planar array, B k This will be described with reference to FIG.

[0180] FIG. 13 is a diagram for explaining a case where four antennas 211 form a 2×2 planar array. As shown in FIG. 13, antennas 211A to 211D form a 2×2 planar array. The angle between the arrival direction of the received signal (i.e., the line connecting the origin and the portable device 100) and the X axis is defined as α, and the angle between the arrival direction of the received signal and the Y axis is defined as β. Antenna 211A is defined as the first antenna (i.e., k=1), antenna 211B is defined as the second antenna (i.e., k=2), antenna 211C is defined as the third antenna (i.e., k=3), and antenna 211D is defined as the fourth antenna (i.e., k=4). When k=1 is defined as the reference antenna, B k are expressed by the following formulas, respectively.

[0181]

number

[0182]

number

[0183]

number

[0184]

number

[0185] Note that I is the identity matrix.

[0186] Also, n (k) is the internal noise vector of the k-th antenna.

[0187] Also, y s (k) is the signal vector of the k-th antenna. s (k) is B k and s s This is expressed by the following equation:

[0188]

number

[0189] In sparse reconstruction, the data vector z (k) is the extension mode matrix A and y (k) is converted into a form that includes a matrix multiplication with

[0190]

number

[0191] where A is the extension mode matrix mentioned above. (k) corresponds to the above-mentioned extended signal vector at the k-th antenna.

[0192] -Application of M-FOCUSS When the above equation (43) is expanded to a plurality of wireless communication units 210 while ignoring internal noise, Z is converted into a format including the matrix product of A and Y, as shown in the following equation.

[0193]

number

[0194] Z is the data vector z (k) is a matrix in which K pieces of Z are arranged. In other words, Z is a vector in which the CIRs obtained in each of the multiple wireless communication units 210 are arranged for the multiple wireless communication units 210. Z is also called a data matrix. Z is expressed by the following equation.

[0195]

number

[0196] Y is a matrix in which the extended signal vectors in each of the multiple radio communication units 210 are arranged for the multiple radio communication units 210. Y is also referred to as an extended signal matrix. Y is expressed by the following equation.

[0197]

number

[0198] where y (k) is the k-th column vector of the expanded signal matrix Y. On the other hand, y[i] is the i-th row vector of the expanded signal matrix Y. y (k) The relationship between y[i] and y[i] will be explained in detail with reference to FIG.

[0199] Figure 14 shows the (k) 14 is a diagram for explaining the relationship between y[i] and y[i]. (k) is the extended signal vector corresponding to the CIR at the k-th antenna. (1) is the extended signal vector corresponding to the CIR of the first antenna (i.e., k=1). (2) is the extended signal vector corresponding to the CIR of the second antenna (i.e., k=2). (3) is the extended signal vector corresponding to the CIR of the third antenna (i.e., k=3). (4) is the extended signal vector corresponding to the CIR of the fourth antenna (i.e., k=4). On the other hand, y[i] is a vector in which elements corresponding to the ith delay time in the CIR of all antennas are arranged. For example, y[1] is a vector in which elements corresponding to the delay time bin T1 in the four CIRs are arranged. y[N] is a vector in which elements corresponding to the delay time bin T N is a vector with elements corresponding to

[0200] The control unit 230 estimates the extended signal matrix Y that minimizes a predetermined norm. At this time, the control unit 230 estimates the extended signal matrix Y that minimizes the predetermined norm and is a sparse solution, on the condition that the above mathematical formula (44) is satisfied.

[0201] The predetermined norm is the norm of a vector in which values ​​obtained by performing a predetermined operation on multiple elements corresponding to the same delay time among the elements constituting the extended signal matrix Y are arranged for multiple delay times. In other words, the predetermined norm may be the norm of a vector in which N values ​​obtained by performing a predetermined operation on multiple elements constituting y[i] are arranged.

[0202] For example, the predetermined operation may be to take the square root of the sum of squares of multiple elements corresponding to the same delay time. In this case, the predetermined norm may be the norm of an N-dimensional vector shown in the following equation.

[0203]

number

[0204] As another example, the predetermined operation may be an average.

[0205] Here, the norm is the length of the vector. The norm may be the lp norm. The lp norm is expressed by the following formula:

[0206]

number

[0207] Here, p is a constant between 0 and 1. However, in Equation (48), 0 0 = 0.

[0208] In the following, it is assumed that the control unit 230 estimates the extended signal matrix Y that minimizes the lp norm of a vector obtained by arranging the square root of the sum of the squares of multiple elements corresponding to the same delay time among the elements that make up the extended signal matrix Y, for multiple delay times, as a predetermined norm. Specifically, the control unit 230 estimates the extended signal matrix Y that minimizes the predetermined norm by repeatedly performing calculations in the following steps 1 to 3.

[0209]

number

[0210]

number

[0211]

number

[0212] where Y m is a candidate for the augmented signal matrix Y that minimizes a given norm. m is the number of iterations. y m-1 [N] is Y m-1 is a vector consisting of elements corresponding to the i-th delay time in the extended signal matrix, where i is the delay time bin index, and N is the maximum value of the delay time bin index i.

[0213] Y m The initial value Y0 is given by the following equation:

[0214]

number

[0215] where A - is the generalized inverse of the extended mode matrix A. The generalized inverse may be the Moore-Penrose generalized inverse. Therefore, the initial value Y0 is the minimum norm solution of Y. However, the initial value Y0 is not a sparse solution.

[0216] The control unit 230 repeatedly executes the above steps 1 to 3. As an example, steps 1 to 3 are executed as follows: m may be repeatedly executed until convergence. As another example, STEP 1 to STEP 3 may be repeatedly executed a predetermined number of times. This makes it possible to estimate an extended signal matrix Y that is closer to the true value.

[0217] - Estimation of the reception time of the first arriving wave Control unit 230 estimates the reception time of the first arriving wave based on the extended signal matrix Y estimated by M-FOCUSS that minimizes a predetermined norm. In M-FOCUSS, extended signal matrix Y is estimated under the condition of matching with the CIRs of multiple wireless communication units 210. Therefore, it is possible to improve the estimation accuracy of the reception time of the first arriving wave compared to when extended signal vector s is estimated under the condition of matching with a single CIR.

[0218] The estimation method is as described above with respect to the estimation of the propagation delay time based on the extended signal vector. That is, the control unit 230 estimates the delay time corresponding to the non-zero elements in the extended signal matrix that minimizes the predetermined norm as the reception time of the first arriving wave. In particular, the control unit 230 estimates the earliest delay time among the delay times corresponding to the non-zero elements in the extended signal matrix that minimizes the predetermined norm as the reception time of the first arriving wave. Note that, when the multiple y (k) has non-zero elements at common delay times.

[0219] (5) Singular Value Decomposition When estimating the extended signal vector s, the control unit 230 performs singular value decomposition to obtain A m The general inverse matrix A of m - In this case, the control unit 230 may obtain A using, for example, TSVD (Truncated Singular Value Decomposition). m - You may ask for:

[0220] In this case, the control unit 230 changes A m is decomposed into a form containing a diagonal matrix consisting of singular values ​​larger than a predetermined threshold, and then A m - Calculate A m is subjected to singular value decomposition as follows:

[0221]

number

[0222] where S t is a diagonal matrix of t non-zero singular values. t is S t V is a matrix consisting of t columns of left singular vectors corresponding to t is S t is a matrix consisting of t columns of right singular vectors corresponding to V, where t is the dimension of the signal subspace. The signal subspace is the space consisting of signals whose power is higher than a threshold. t H is the matrix V t is the complex conjugate transpose of V t It is also called the adjoint matrix of A. m - is calculated using the following formula:

[0223]

number

[0224] where S t contains the t non-zero singular values ​​of the signal subspace, i.e., S t is a diagonal matrix consisting of t singular values ​​that are greater than a predetermined threshold. t is equal to the number L of multipath waves. Therefore, by calculating the generalized inverse matrix using only the singular values ​​that belong to the signal subspace (i.e., take large values) as described above, it is possible to reduce the influence of noise. This is because the singular values ​​that do not belong to the signal subspace (i.e., take small values) correspond to noise. By reducing the influence of noise, it is possible to stably and accurately calculate the generalized inverse matrix even under the influence of noise.

[0225] (6) Regularization In the above, the control unit 230 performs singular value decomposition to obtain A m - On the other hand, the control unit 230 calculates Am - In this case, the control unit 230 may use the following formula (55) instead of the formula (50) in STEP 2. m H is matrix A m is the complex conjugate transpose of A m It is also called the adjoint matrix of

[0226]

number

[0227] However, in the above formula (55), A m A m H If is not singular, the inverse matrix (A m A m H ) -1 Therefore, in STEP 2 above, the control unit 230 may use the following formula (56) instead of formula (55).

[0228]

number

[0229] Here, α in Equation (56) is a positive infinitesimal quantity. I is a unit matrix. α is also called a regularization parameter. By using the regularization parameter as in Equation (56) above, A m A m H Even if A is not regular, m A m H By making +αI regular, A m A m H The inverse matrix of (A m A m H ) -1 Moreover, by using the regularization parameter, Y mIt is possible to more easily achieve convergence of the regularization parameters in FOCUSS and M-FOCUSS. Note that the first and second non-patent documents refer to the regularization parameters in FOCUSS and M-FOCUSS.

[0230] The control unit 230 m A m H The inverse matrix of (A m A m H ) -1 In this case, the control unit 230 may use TSVD to calculate A in Equation (55) of STEP 2 above. m A m H is decomposed into a form containing a diagonal matrix consisting of singular values ​​greater than a first threshold, and then (A m A m H ) -1 Calculate A m A m H is subjected to singular value decomposition as follows:

[0231]

number

[0232] At this time, (A m A m H ) -1 is calculated using the following formula:

[0233]

number

[0234] In addition, A m A m H Since is a square matrix, the singular value decomposition here is also called eigenvalue decomposition. And TSVD is called TEVD (Truncated Eigen Value Decomposition).

[0235] That's all, A m - A specific example of the calculation of A was explained. m - When singular value decomposition is used to calculate A, unnecessary singular values ​​can be removed, which may shorten the calculation time. m - When singular value decomposition is used in the calculation of , it is expected that the estimation accuracy will be improved by not excluding singular values.

[0236] (7) Threshold processing In M-FOCUSS, threshold processing may be performed. The threshold processing here refers to a process of setting elements equal to or less than a second threshold to 0. For example, the control unit 230 may set the weighting matrix W m The diagonal elements of the weight matrix W that are equal to or smaller than a second threshold may be set to zero. m For example, the control unit 230 may set the weighting matrix W based on the maximum value of the diagonal elements of the weighting matrix W. m For the diagonal elements of , values ​​whose ratio to the maximum value is equal to or less than a second threshold may be set to zero.

[0237] According to the above thresholding process, the weight matrix W m When creating the augmented signal matrix Y m Among the elements of the matrix Y, elements with values ​​less than the second threshold are considered to be noise rather than a signal and are converted to zero. m This allows the function to converge faster. In addition, since the number of non-zero elements is reduced, it becomes easier to obtain a sparse solution.

[0238] 4.2. Estimation of location parameters The control unit 230 estimates the location parameters based on the first arriving wave detected by the above-described processing.

[0239] -Range measurement processing Based on the reception time of the first arriving wave estimated by the above-described process, the control unit 230 estimates the distance R between the portable device 100 and the communication unit 200. The method for estimating the distance R is as described above with reference to FIG.

[0240] Specifically, the communication unit 200 calculates the CIR for the first ranging signal, performs sparse reconstruction and M-FOCUSS, and measures the time INT3 by determining the time corresponding to the earliest delay time bin among the delay time bins corresponding to non-zero elements among the elements included in the extended signal matrix Y estimated by M-FOCUSS as the reception time of the first arriving wave of the first ranging signal.

[0241] Similarly, the communication unit 200 calculates the CIR for the third ranging signal, and performs sparse reconstruction and M-FOCUSS. Then, the communication unit 200 measures the time INT4 by determining the time corresponding to the earliest delay time bin among the delay time bins corresponding to non-zero elements among the elements included in the extended signal matrix Y estimated by M-FOCUSS as the reception time of the first arriving wave of the third ranging signal.

[0242] Then, the control unit 230 estimates the propagation delay time based on times T1 to T4, and estimates the distance R. As described above, the reception time of the first arriving wave can be estimated with high accuracy using M-FOCUSS, which makes it possible to improve the accuracy of distance measurement.

[0243] -Angle estimation processing The communication unit 200 estimates the angles α and β based on the phase at the time of reception of the first arriving wave estimated by the above-described process. The method for estimating the angles α and β is as described above with reference to FIG. 8.

[0244] More specifically, the control unit 230 estimates the angles α and β based on the phase of the non-zero elements included in the extended signal matrix Y estimated by the above-described process. In particular, the control unit 230 estimates the angles α and β based on the phase of the element corresponding to the earliest delay time among one or more non-zero elements included in the extended signal matrix Y. For example, in the extended signal matrix Y estimated by applying M-FOCUSS to the CIR obtained by the antenna configuration shown in FIG. 13, the earliest non-zero element corresponds to the delay time T i In this case, the antenna array phase difference Pd AC is calculated by the following formula:

[0245]

number

[0246] Or, antenna array phase difference Pd AC may be calculated by the following formula:

[0247]

number

[0248] Here, angle() is a function that calculates the phase angle of a complex number. Y(i,k) is the element in the i-th row and k-th column of the extended signal matrix Y.

[0249] The phase differences of the other antenna arrays are calculated in the same manner as above, and angles α and β are calculated.

[0250] As described above, M-FOCUSS allows the reception time of the first arriving wave to be estimated with high accuracy. By performing angle estimation based on the phase of an element that corresponds to the reception time of the first arriving wave estimated with high accuracy, among the elements that make up the extended signal matrix Y, it becomes possible to improve the accuracy of angle estimation as well.

[0251] <4.3. Processing flow> FIG. 15 is a flowchart showing an example of the flow of the location parameter estimation process executed by the communication unit 200 according to this embodiment.

[0252] As shown in Fig. 15, first, the control unit 230 calculates the CIR for each antenna (step S302). Next, the control unit 230 converts a data matrix consisting of the CIR for each antenna into a format including a matrix product of an extended mode matrix and an extended signal matrix using sparse reconstruction (step S304). Next, the control unit 230 estimates an extended signal matrix that minimizes a predetermined norm using M-FOCUSS (step S306). Then, the control unit 230 estimates position parameters based on the estimated extended signal matrix (step S308).

[0253] <4.4.Applicability of M-FOCUSS> As described above, the transmitting side may transmit a signal including multiple preambles, each including one or more preamble symbols, as a transmission signal. In this case, the receiving side may calculate the CIR for each preamble symbol by correlating the portions of the received signal corresponding to the multiple preamble symbols with the preamble symbols at regular intervals after the transmitting side transmits the transmission signal.

[0254] M-FOCUSS may be applied to the CIR obtained by accumulating the CIR for each preamble symbol, or may be applied to the CIR for each preamble symbol.

[0255] Note that the CIR may be calculated for each pulse. In this case, M-FOCUSS may be applied to the CIR obtained by integrating the CIR for each pulse, or may be applied to the CIR for each pulse.

[0256] Alternatively, the CIR may be calculated for the entire preamble, in which case M-FOCUSS may be applied to the CIR calculated for the entire preamble.

[0257] Either method can achieve similar results.

[0258] <4.5. Scope of M-FOCUSS> M-FOCUSS may be applied to the entire CIR.

[0259] On the other hand, M-FOCUSS may be applied to a portion of the CIR in the time axis direction, which reduces the calculation load compared to when M-FOCUSS is applied to the entire CIR.

[0260] In particular, if the purpose is to detect the first arriving wave, it is desirable to apply M-FOCUSS only to a portion of the CIR near the time of reception of the first arriving wave. A strong correlation is obtained only at delay times where the pulse sequence of the transmitted signal and the pulse sequence of the received signal perfectly match, and the correlation is low in other portions. Therefore, even if M-FOCUSS is applied only to a portion of the CIR near the time of reception of the first arriving wave, the detection accuracy of the first arriving wave can be maintained.

[0261] In this way, by applying M-FOCUSS only to a portion of the CIR around the reception time of the first arriving wave, it is possible to reduce the computational load while maintaining detection accuracy compared to applying M-FOCUSS to the entire CIR.

[0262] <4.6. Weighted M-FOCUSS> The control unit 230 may use weighted M-FOCUSS instead of M-FOCUSS to estimate the extended signal matrix Y that minimizes a predetermined norm.

[0263] The predetermined norm is the norm of a matrix obtained by weighting the extended signal matrix Y with a weight that is smaller for outliers. This configuration makes it possible to prevent an erroneous extreme value from being estimated as a solution due to the influence of the outlier. That is, it is possible to improve the estimation accuracy of the extended signal matrix Y, and as a result, to improve the estimation accuracy of the position parameters.

[0264] The predetermined norm may be the norm of a vector obtained by arranging, for each of the plurality of delay time bins, the square roots of the values ​​obtained by squaring each of the plurality of elements constituting the extended signal matrix Y that correspond to the same delay time bin, multiplying the result by a weight, and integrating the squares. Specifically, the control unit 230 estimates the extended signal matrix Y that minimizes the predetermined norm by repeatedly calculating STEP 1 to STEP 3 shown in the following Equations (61) to (63), instead of STEP 1 to STEP 3 shown in the above-mentioned Equations (49) to (51).

[0265]

number

[0266]

number

[0267]

number

[0268] where m is the number of iterations. m+1 is a candidate for the augmented signal matrix Y that minimizes a given norm. m+1 [n,k] is the candidate augmented signal matrix Y m+1 is the element corresponding to the i-th delay time bin and the k-th antenna 211 in g m is a weight. N is the maximum value of the index n of the delay time bin. K is the number of antennas 211. p is a constant between 0 and 1. A is an extension mode matrix. Z is a data matrix. The initial value Y0 of Ym is as shown in the above equation (52).

[0269] In addition, the candidate extended signal matrix Y m+1 is defined by the following equation:

[0270]

number

[0271] Weight g m can be defined, for example, as follows:

[0272]

number

[0273] Here, α is a positive number. That is, α is a real number greater than 0. α determines the weight g m It is possible to ensure that the denominator of [n,k] does not become 0.

[0274] As shown in the above formula (65), the element y m The weight g corresponding to [n,k] m [n,k] is the element y m Element y of [n,k] m The larger the difference from the average value of multiple elements corresponding to the same delay time bin as [n, k], the smaller the value may be, and the smaller the difference, the larger the value may be. With this configuration, it is possible to prevent inheritance of errors in the process of repeating STEP 1 to STEP 3 above, and to prevent convergence to erroneous extreme values. In other words, it is possible to improve the estimation accuracy of the extended signal matrix Y, and as a result, to improve the estimation accuracy of the position parameters.

[0275] Thus, the weight g m [n,k] is a candidate Y of the extended signal matrix Y m , may take a small value corresponding to an outlier in multiple elements corresponding to the same delay time bin in . With this configuration, it is possible to improve the estimation accuracy of the extended signal matrix Y under the assumption that the signal arrival times at multiple antennas 211 are the same.

[0276] Weighted M-FOCUSS is particularly effective when the arrival times of multiple incoming waves are close to each other, because the closer the arrival times of multiple incoming waves are, the more likely it is that some antennas 211 will have outliers.

[0277] However, the weight g m [n, k] is the element y m It is not limited to calculations based on the inverse of the difference from the average value of [n, k]. For example, instead of the average value, for example, the median may be used. As another example, m Instead of the difference from the mean value of [n,k], the element y m The square of the difference from the mean value of [n,k] may be used.

[0278] The control unit 230 repeatedly executes the above steps 1 to 3. As an example, steps 1 to 3 are executed as follows: m may be repeatedly executed until convergence. As another example, STEP 1 to STEP 3 may be repeatedly executed a predetermined number of times. This makes it possible to estimate an extended signal matrix Y that is closer to the true value.

[0279] The processing after estimating the extended signal matrix Y is the same as when M-FOCUSS is used. That is, the control unit 230 estimates the reception time of the first arriving wave based on the extended signal matrix Y estimated by weighted M-FOCUSS that minimizes a predetermined norm. That is, the control unit 230 estimates the earliest delay time bin n among multiple delay time bins n corresponding to non-zero elements y[n,k] in the extended signal matrix Y that minimizes the predetermined norm as the reception time of the first arriving wave. Then, the control unit 230 estimates the position parameters based on the estimated reception time of the first arriving wave.

[0280] The weighted M-FOCUSS has been explained above.

[0281] Weighted M-FOCUSS may be operated in the same manner as the above-described M-FOCUSS, and the same modifications as those of the above-described M-FOCUSS may be applied to weighted M-FOCUSS.

[0282] As an example, the control unit 230 performs singular value decomposition to estimate the extended signal vector s. m+1The general inverse matrix (AW m+1 ) - As another example, the control unit 230 may obtain (AW m+1 ) - To obtain , regularization may be performed.

[0283] As another example, the control unit 230 may perform threshold processing. That is, the control unit 230 may use the weighting matrix W m+1 Among the diagonal components of , elements equal to or less than the second threshold may be set to zero.

[0284] As another example, weighted M-FOCUSS may be applied to the entire CIR, or may be applied to a portion of the CIR in the time axis direction.

[0285] <<5. Supplementary Information>> Although the preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, the present invention is not limited to these examples. It is clear that a person skilled in the art to which the present invention pertains can conceive of various modifications and alterations within the scope of the technical ideas set forth in the claims, and it is understood that these also naturally fall within the technical scope of the present invention.

[0286] For example, in the above embodiment, the CIR is described as a correlation calculation result, but the present invention is not limited to such an example. As an example, the CIR may be the received signal (a complex number having IQ components) itself. The CIR value may be the complex number having IQ components that is the received signal itself, the amplitude or phase of the received signal, or the power that is the sum of the squares of the I and Q components of the received signal (or the square of the amplitude). In this case, the receiving side detects the first arriving wave from the received signal. For example, the receiving side may use the first time that the amplitude or power of the received radio signal exceeds a predetermined threshold as a predetermined detection criterion for detecting the first arriving wave. In this case, the receiving side may detect the signal (more specifically, the sampling point) whose amplitude or received power first exceeds the predetermined threshold among the received signals as the first arriving wave.

[0287] For example, in the above embodiment, the control unit 230 is described as calculating the CIR, detecting the first incoming wave, and estimating the location parameters, but the present invention is not limited to such an example. At least one of these processes may be performed by the wireless communication unit 210. For example, each of the multiple wireless communication units 210 may calculate the CIR and detect the first incoming wave based on the signal received by each antenna 211. Furthermore, the location parameters may be estimated by the wireless communication unit 210 functioning as the master, for example.

[0288] For example, in the above embodiment, an example has been described in which angles α and β are calculated based on the antenna array phase difference between an antenna pair, but the present invention is not limited to such an example. As an example, communication unit 200 may calculate angles α and β by performing beamforming using multiple antennas 211. In this case, communication unit 200 scans the main lobes of multiple antennas 211 in all directions, determines that portable device 100 is located in the direction with the strongest received power, and calculates angles α and β based on that direction.

[0289] For example, in the above embodiment, as explained with reference to FIG. 3, the local coordinate system is described as a coordinate system having coordinate axes parallel to the axis connecting the antenna pair, but the present invention is not limited to such an example. For example, the local coordinate system may be a coordinate system having coordinate axes that are not parallel to the axis connecting the antenna pair. Furthermore, the origin is not limited to the center of the multiple antennas 211. The local coordinate system according to this embodiment may be set arbitrarily based on the arrangement of the multiple antennas 211 of the communication unit 200.

[0290] For example, in the above embodiment, an example has been described in which four antennas 211 form a 2×2 planar array, but the present invention is not limited to such an example. The number of antennas 211 is not limited to four, and their arrangement is not limited to a planar array. For example, multiple antennas 211 may be arranged as a linear array. A linear array refers to multiple antennas 211 arranged on the same line. As an example, an example in which four antennas 211 form a linear array will be described with reference to FIG. 16 .

[0291] FIG. 16 is a diagram for explaining a case where four antennas 211 form a linear array. As shown in FIG. 16, antennas 211A to 211D form a linear array. The axes on which antennas 211A to 211D are arranged are defined as coordinate axes, and the angle between the coordinate axes and the direction of arrival of the received signal is defined as θ. Antenna 211A is defined as the first antenna (i.e., k=1), antenna 211B is defined as the second antenna (i.e., k=2), antenna 211C is defined as the third antenna (i.e., k=3), and antenna 211D is defined as the fourth antenna (i.e., k=4). When k=1 is defined as the reference antenna, B k are expressed by the following formulas, respectively.

[0292]

number

[0293] For example, in the above embodiment, an example in which M-FOCUSS or weighted M-FOCUSS is applied to multiple CIRs in multiple wireless communication units 210 has been described. However, the present invention is not limited to such an example. M-FOCUSS or weighted M-FOCUSS may be applied to multiple CIRs obtained from a single wireless communication unit 210. In this case, control unit 230 converts a matrix in which multiple CIRs obtained from a single wireless communication unit 210 are arranged into a data matrix, and converts the data matrix into a format including a matrix product of an extended mode matrix and an extended signal matrix in which extended signal vectors are arranged for multiple CIRs. Control unit 230 then estimates the reception time of the first arriving wave by applying M-FOCUSS or weighted M-FOCUSS to the result of this conversion. In this example, as in the above embodiment, it is possible to improve the estimation accuracy of the reception time of the first arriving wave.

[0294] As an example, one wireless communication unit 210 may receive a signal including multiple preambles from portable device 100. In this case, control unit 230 calculates one CIR for each preamble received by wireless communication unit 210. Then, control unit 230 converts the multiple CIRs calculated from the multiple preambles into a format including the matrix multiplication, and applies M-FOCUSS or weighted M-FOCUSS.

[0295] As another example, one wireless communication unit 210 may receive a signal from portable device 100 multiple times. The signal here refers to a signal including one or more preambles. In this case, control unit 230 calculates one CIR for one signal received by wireless communication unit 210. Then, control unit 230 converts the multiple CIRs calculated from the signals received multiple times into a format including the matrix multiplication, and applies M-FOCUSS or weighted M-FOCUSS.

[0296] When M-FOCUSS or weighted M-FOCUSS is applied to multiple CIRs obtained from one wireless communication unit 210, B k is expressed by the following equation:

[0297]

number

[0298] For example, in the above embodiment, an example has been described in which the person to be authenticated is the portable device 100 and the authenticator is the communication unit 200, but the present invention is not limited to such an example. The roles of the portable device 100 and the communication unit 200 may be reversed. For example, the portable device 100 may identify the location parameters. Furthermore, the roles of the portable device 100 and the communication unit 200 may be dynamically exchanged. Furthermore, the identification of location parameters and authentication may be performed between the communication units 200.

[0299] For example, in the above embodiment, an example in which the present invention is applied to a smart entry system has been described, but the present invention is not limited to such an example. The present invention can be applied to any system that estimates location parameters and performs authentication by transmitting and receiving signals. For example, the present invention can be applied to a pair including any two devices from among a mobile device, a vehicle, a smartphone, a drone, a house, a home appliance, etc. In this case, one of the pair acts as the authenticator and the other acts as the authenticatee. Note that the pair may include two devices of the same type, or two different types of devices. The present invention can also be applied to a wireless LAN (Local Area Network) router used to identify the location of a smartphone.

[0300] For example, although the above embodiment uses UWB as the wireless communication standard, the present invention is not limited to this example. For example, a wireless communication standard using infrared rays may be used.

[0301] In the above embodiment, an example has been described in which the multiple snapshots of M-FOCUSS or weighted M-FOCUSS are multiple CIRs obtained by multiple antennas 211, but the present invention is not limited to such an example. For example, the multiple snapshots of M-FOCUSS or weighted M-FOCUSS may be any data obtained by multiple antennas 211, multiple time samples, or multiple frequencies.

[0302] The series of processes performed by each device described in this specification may be realized using software, hardware, or a combination of software and hardware. The programs constituting the software are stored in advance, for example, on a recording medium (non-transitory medium) provided inside or outside each device. Each program is then loaded into RAM when executed by a computer, and executed by a processor such as a CPU. The recording medium may be, for example, a magnetic disk, an optical disk, a magneto-optical disk, or a flash memory. The computer program may also be distributed, for example, via a network, without using a recording medium.

[0303] Furthermore, the processes described herein using flowcharts do not necessarily have to be performed in the order shown. Some process steps may be performed in parallel. Additional process steps may be employed, and some process steps may be omitted. [Explanation of symbols]

[0304] 1: System, 100: Portable device, 110: Wireless communication unit, 111: Antenna, 120: Storage unit, 130: Control unit, 200: Communication unit, 202: Vehicle, 210: Wireless communication unit, 211: Antenna, 220: Storage unit, 230: Control unit

Claims

1. a plurality of antennas for wirelessly receiving signals from other communication devices; When the other communication device transmits a signal including a pulse as a first signal, a correlation is calculated between the first signal and a plurality of second signals, which are signals corresponding to the first signal and are received by the plurality of antennas, at regular intervals; A data matrix is ​​a matrix in which a plurality of correlation calculation results, which are results of calculating correlations between a plurality of the second signals and the first signals at a plurality of antennas at each specified time, are arranged, an extended mode matrix, which is a matrix consisting of a plurality of elements representing the correlation calculation result when it is assumed that a signal is received at each of a plurality of set times; an extended signal matrix, which is a matrix in which an extended signal vector, which is a vector consisting of a plurality of elements representing the presence or absence of a signal at each of the set times in the antenna and the amplitude and phase of the signal, is arranged for a plurality of the correlation calculation results; and convert it into a form that includes the matrix product of estimating the augmented signal matrix that minimizes a predetermined norm; a control unit that estimates a reception time of the second signal based on the extended signal matrix that minimizes the predetermined norm; Equipped with The predetermined norm is a norm of a matrix obtained by weighting the extended signal matrix with a weight that is smaller for outliers. Communication equipment.

2. the predetermined norm is a norm of a vector obtained by arranging, for each of the plurality of set times, the square roots of the values ​​obtained by squaring each of the plurality of elements constituting the extended signal matrix, the elements corresponding to the same set time, and multiplying the squares by the weights. The communication device according to claim 1 .

3. the control unit estimates the extended signal matrix that minimizes the predetermined norm by repeatedly calculating Equations (1), (2), and (3); m is the number of iterations, Y ｍ＋１ is a candidate augmented signal matrix that minimizes the predetermined norm, y ｍ＋１ [n, k] is the candidate of the extended signal matrix Y ｍ＋１ an element corresponding to the i-th setup time and the k-th antenna in g ｍ is the weight, N is the maximum value of the index n of the set time, K is the number of antennas, p is a constant between 0 and 1, A is the expansion mode matrix, Z is the data matrix. The communication device according to claim 2 . [Equation 1] [Equation 2] [Equation 3]

4. The weights take smaller values ​​to correspond to outliers in a plurality of elements corresponding to the same setting time in the extended signal matrix. The communication device according to claim 3 .

5. The weights are defined by equation (4): α is a positive number, The communication device according to claim 4. [Equation 4]

6. The set time interval is shorter than the specified time. The communication device according to claim 1 .

7. the control unit estimates, as the reception time of the second signal, the earliest setting time among the setting times corresponding to non-zero elements in the extended signal matrix that minimizes the predetermined norm. The communication device according to claim 1 .

8. When another communication device transmits a signal including a pulse as a first signal, a correlation is calculated between the first signal and a plurality of second signals, which are signals corresponding to the first signal and are received by a plurality of antennas, at regular intervals; a data matrix that is a matrix in which a plurality of correlation calculation results, which are results of calculating correlations between a plurality of the second signals and the first signals at a plurality of the antennas at each specified time, are arranged; an extended mode matrix, which is a matrix consisting of a plurality of elements representing the correlation calculation result when it is assumed that a signal is received at each of a plurality of set times; an extended signal matrix, which is a matrix in which an extended signal vector, which is a vector consisting of a plurality of elements representing the presence or absence of a signal at each of the set times in the antenna and the amplitude and phase of the signal, is arranged for a plurality of the correlation calculation results; and convert it into a form that includes the matrix product of estimating the augmented signal matrix that minimizes a predetermined norm; estimating a time of reception of the second signal based on the augmented signal matrix that minimizes the predetermined norm; Including, The predetermined norm is a norm of a matrix obtained by weighting the extended signal matrix with a weight that is smaller for outliers. Information processing methods.

9. Computer, When another communication device transmits a signal including a pulse as a first signal, a correlation is calculated between the first signal and a plurality of second signals, which are signals corresponding to the first signal and are received by a plurality of antennas, at regular intervals; a data matrix that is a matrix in which a plurality of correlation calculation results, which are results of calculating correlations between a plurality of the second signals and the first signals at a plurality of the antennas at each specified time, are arranged; an extended mode matrix, which is a matrix consisting of a plurality of elements representing the correlation calculation result when it is assumed that a signal is received at each of a plurality of set times; an extended signal matrix, which is a matrix in which an extended signal vector, which is a vector consisting of a plurality of elements representing the presence or absence of a signal at each of the set times in the antenna and the amplitude and phase of the signal, is arranged for a plurality of the correlation calculation results; and convert it into a form that includes the matrix product of estimating the augmented signal matrix that minimizes a predetermined norm; a control unit that estimates a reception time of the second signal based on the extended signal matrix that minimizes the predetermined norm; It functions as The predetermined norm is a norm of a matrix obtained by weighting the extended signal matrix with a weight that is smaller for outliers. program.

Images