JP7531182B2 - COMMUNICATION DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM - Google Patents

Description

The present invention relates to a communication device, an information processing method, and a program.

In recent years, technology has been developed that allows 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, the following Patent Document 1 discloses a technology in which wireless communication is performed using UWB (Ultra-Wide Band) and a UWB receiver determines the angle of incidence of a wireless signal from a UWB transmitter.

International Publication No. 2015/176776

However, while the technology described in Patent Document 1 above is able to identify the angle of incidence of a wireless signal, there is still room for improvement in terms of improving the accuracy of measuring the distance between a UWB receiver and a UWB transmitter.

In other words, in technology for measuring the distance between one device and another device, it is desirable to further improve the measurement accuracy of the distance between those devices.

Therefore, the present invention has been made in consideration of the above problems, and the object of the present invention is to provide a mechanism that can improve the accuracy of measuring the distance between multiple devices.

In order to solve the above problem, according to one aspect of the present invention, a communication device is provided that includes a wireless communication unit that wirelessly receives a signal from another communication device, and a control unit that calculates a correlation between the first signal and a second signal that is a signal corresponding to the first signal received by the wireless communication unit when the other communication device transmits a signal including a pulse as a first signal, for each specified time, converts the correlation calculation result, which is the result of calculating the correlation between the second signal and the first signal for each specified time, into a format that includes a matrix product of an extended mode matrix, which is a matrix consisting of multiple elements that represents the correlation calculation result when it is assumed that a signal is received at each of multiple set times, and an extended signal vector, which is a vector consisting of multiple elements that represents the presence or absence of a signal for each set time and the amplitude and phase of the signal, and estimates the reception time of the second signal based on the set times corresponding to the multiple elements in the extended signal vector, and the interval of the set times is shorter than the specified time.

In addition, in order to solve the above problem, according to another aspect of the present invention, there is provided an information processing method comprising: wirelessly receiving a signal from another communication device; calculating a correlation between the first signal and a second signal, which is a signal corresponding to the first signal received when the other communication device transmits a signal including a pulse as a first signal, at specified time intervals; converting a correlation calculation result, which is a result of calculating the correlation between the second signal and the first signal at the specified time intervals, into a format including a matrix product of an extended mode matrix, which is a matrix consisting of multiple elements representing the correlation calculation result when it is assumed that a signal is received at each of multiple set times, and an extended signal vector, which is a vector consisting of multiple elements representing the presence or absence of a signal at each set time and the amplitude and phase of the signal; and estimating a reception time of the second signal based on the set times corresponding to the multiple elements in the extended signal vector, wherein the interval of the set times is shorter than the specified time.

In order to solve the above problem, according to another aspect of the present invention, a program is provided that causes a computer to function as a control unit that, when another communication device transmits a signal including a pulse as a first signal, calculates a correlation between the first signal and a second signal that is a signal corresponding to the first signal received by a wireless communication unit that wirelessly receives a signal from the other communication device at each specified time, converts the correlation calculation result, which is the result of calculating the correlation between the second signal and the first signal at each specified time, into a format that includes a matrix product of an extended mode matrix, which is a matrix consisting of multiple elements that represents the correlation calculation result when it is assumed that a signal is received at each of multiple set times, and an extended signal vector, which is a vector consisting of multiple elements that represents the presence or absence of a signal at each set time and the amplitude and phase of the signal, and estimates the reception time of the second signal based on the set times corresponding to the multiple elements in the extended signal vector, and the interval of the set times is shorter than the specified time.

As described above, the present invention provides a mechanism that can improve the accuracy of measuring distances between multiple devices.

FIG. 1 is a diagram illustrating an example of a configuration of a system according to an embodiment of the present invention. 2 is a diagram showing an example of an arrangement of a plurality of antennas provided in a vehicle according to the present embodiment; FIG. FIG. 4 is a diagram showing an example of position parameters of the portable device according to the embodiment; FIG. 4 is a diagram showing an example of position parameters of the portable device according to the embodiment; FIG. 2 is a diagram illustrating an example of a processing block for signal processing in the communication unit according to the embodiment. 1 is a graph showing an example of a CIR according to the present embodiment. FIG. 11 is a sequence diagram showing an example of the flow of a distance measurement process executed in the system according to the present embodiment. FIG. 4 is a sequence diagram showing an example of the flow of an angle estimation process executed in the system according to the present embodiment. 1 is a graph for explaining a technical problem of the present embodiment. 1 is a graph for explaining a technical problem of the present embodiment. 1 is a graph for explaining a technical problem of the present embodiment. 1 is a graph for explaining a technical problem of the present embodiment. 11 is a graph for explaining a simulation result of the present embodiment. 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. 11 is a graph for explaining a simulation result of the present embodiment.

The preferred embodiment of the present invention will be described in detail below with reference to the attached drawings. Note that in this specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals to avoid redundant description.

In addition, 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 wireless communication units 210A, 210B, and 210C as necessary. However, if there is no need to particularly distinguish between multiple elements having substantially the same functional configuration, only the same reference numeral may be used. For example, if 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.

<<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.

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 FIG. 1, the portable device 100 is an example of a communication device on the side of the person to be authenticated, and the communication unit 200 is an example of a communication device on the side of the authenticator.

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

(1) Portable device 100
The portable device 100 is configured as any device carried by a user. The any device includes an electronic key, a smartphone, a wearable terminal, etc. As shown in FIG 1, the portable device 100 includes a wireless communication unit 110, a storage unit 120, and a control unit 130.

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.

Wireless communication between the wireless communication unit 110 and the communication unit 200 is achieved, for example, by signals using UWB (Ultra-Wide Band). In wireless communication of signals using UWB, if the impulse method is used, the propagation delay time of the radio waves can be measured with high accuracy by using radio waves with a very short pulse width of less than nanoseconds, 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 a radio wave to receiving it. The wireless communication unit 110 is configured, for example, as a communication interface capable of communication using UWB.

Note that signals using UWB can be transmitted and received, for example, as ranging signals, angle estimation signals, and data signals. The ranging signals are signals transmitted and received in the ranging process described below. 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 the angle estimation process described below. 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.

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.

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), a password, and an authentication algorithm for authentication. The storage unit 120 is composed of, for example, a storage medium such as a flash memory, and a processing device that executes recording and playback on the storage medium.

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 memory unit 120 and writes information to the memory unit 120. The control unit 130 also functions as an authentication control unit that controls the authentication process performed with the communication unit 200 of the vehicle 202. The control unit 130 is composed of electronic circuits such as a CPU (Central Processing Unit) and a microprocessor, for example.

(2) Communication unit 200
The communication unit 200 is provided in correspondence 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 may wirelessly transmit a control signal to the vehicle 202 based on the result of communication with the portable device 100, and remotely control 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.

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 wireless signals from the portable device 100 and transmits wireless signals to the portable device 100. The wireless communication unit 210 is configured as a communication interface capable of UWB communication, for example.

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

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 programs for the operation of the communication unit 200, authentication algorithms, etc. The storage unit 220 is composed of, for example, a storage medium such as a flash memory, and a processing device that performs recording and playback on the storage medium.

The control unit 230 has a function of controlling the overall operation of the communication unit 200 and the in-vehicle devices mounted on 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 the authentication process 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 lock of the vehicle 202 and locks and unlocks the door lock. The control unit 230 also functions as an engine control unit that controls the engine of the vehicle 202 and starts/stops the engine. 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).

＜＜2. Technical features＞＞
2.1. Position parameters
The communication unit 200 (more specifically, the control unit 230) according to this embodiment performs a position parameter estimation process to estimate a position parameter indicating the position of the portable device 100. Various definitions related to the position parameter will be described below with reference to Figs. 2 to 4.

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

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.

Figure 3 is a diagram showing an example of the position parameters of the portable device 100 according to this embodiment. The position parameters may include the distance R between the portable device 100 and the communication unit 200. The distance R shown in Figure 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 one of the multiple wireless communication units 210 and the portable device 100. The distance R may 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.

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 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 the angle between the line connecting the origin and the portable device 100 and the X-axis. The angle β is the angle between the line connecting the origin and the portable device 100 and the Y-axis.

Figure 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 Figure 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.

<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. At that time, the portable device 100 and the communication unit 200 calculate a CIR (Channel Impulse Response).

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

As an example, the CIR may be a correlation calculation result that is a result of calculating the correlation between a transmission signal and a reception signal at each specified time. The correlation here may be a sliding correlation, which is a process of calculating the correlation between a transmission signal and a reception signal while shifting the relative positions of each signal in the time direction. The CIR includes a correlation value that indicates the level of correlation between a transmission signal and a reception signal as an element for each time interval with a specified time as an interval. The specified time is, for example, the interval at which the receiving side samples the reception signal. Therefore, the elements that make up the CIR are also called sampling points. The correlation value may be a complex number having an IQ component. 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.

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

As another example, the CIR may be the received signal (a complex number having I and Q components) itself for each specified time. The CIR may also be the amplitude or phase of the received signal for each specified time. The CIR may also be a power value that is the sum of the squares of the I and Q components of the received signal for each specified time.

The portable device 100 and the communication unit 200 acquire the time using a time counter. The time counter is a counter that counts (typically increments) a value (hereinafter also referred to as a count value) indicating an elapsed time at a predetermined time interval (hereinafter also referred to as a count period). The current time is calculated based on the count value, count period, and count start time counted by the time counter. The fact that the count period and count start time match between different devices is also referred to as being synchronized. On the other hand, the fact that at least one of the count period and count start time differs between different devices is also referred to as being not synchronized or being asynchronous. 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 above-mentioned specified time when calculating the CIR may be an integer multiple of the count period of the time counter. In the following description, unless otherwise specified, the portable device 100 and each of the multiple wireless communication units 210 are described as being synchronized with each other.

Below, the CIR calculation process when the transmitting side is the portable device 100 and the receiving side is the communication unit 200 will be explained in detail with reference to Figures 5 and 6.

Figure 5 is a diagram showing an example of a processing block for signal processing in the communication unit 200 according to this embodiment. As shown in Figure 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.

The oscillator 212 generates a signal with the same frequency as the frequency of the carrier wave that carries the transmission signal, and outputs the generated signal to the multiplier 213 and the 90-degree phase shifter 214.

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

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

The correlator 218 calculates the CIR by taking a sliding correlation between the received signal consisting of the I component and the Q component output from the LPF 216 and the reference signal. Note that the reference signal here is the same signal as the transmitted signal before being multiplied by the carrier wave.

The accumulator 219 accumulates the CIR output from the correlator 218 and outputs it.

Here, the transmitting side may transmit a signal including a preamble containing one or more preamble symbols as a transmission signal. A preamble is a sequence known between the transmitting side and the receiving side. 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 symbol is the target of accumulation by accumulation 219. That is, correlator 218 calculates the CIR for each preamble symbol by taking a sliding correlation between each of the parts corresponding to the multiple preamble symbols included in the received signal and the preamble symbol included in the transmission signal (i.e., the reference signal). Then, accumulator 219 accumulates the CIR for each preamble symbol for one or more preambles included in the preamble, and outputs the accumulated CIR.

(2) Example of CIR An example of the CIR output from the integrator 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 elapsed time from the time when the transmitting side transmits the transmission signal. The vertical axis of this graph is the absolute value of the CIR value (e.g., power value). Note that in the following description, CIR refers to the delay profile.

In a CIR, a piece of information that constitutes information that changes over time, such as a CIR value at a certain delay time, is also called a sampling point. Typically, in a CIR, a set of sampling points between zero crossing points corresponds to one pulse. The CIR shown in FIG. 6 includes a set of sampling points 21 that corresponds to a certain pulse, and a set of sampling points 22 that corresponds to another pulse.

Set 21 corresponds to, for example, a signal (e.g., a pulse) that arrives at the receiving side 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, a signal (e.g., a pulse) that arrives at the receiving side via a path other than a fast path. In this way, a signal that arrives via multiple paths is also called a multipath wave.

(3) Detection of the first arriving wave The receiving side detects, among the wireless signals received from the transmitting side, a signal that satisfies a predetermined detection criterion as a signal that has arrived at the receiving side via the fast path. Then, the receiving side estimates the location parameters based on the detected signal.

A signal detected as having reached the receiving side via a fast path is also referred to as a first arriving wave below. The first arriving wave 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 directly (i.e., without being reflected, etc.) via the shortest path between the transmitter and the receiver. In other words, a direct wave is a signal that reaches the receiving side via a fast path. A delayed wave is a signal that is received by the receiving side indirectly via a path that is not the shortest between the transmitter and the receiver, i.e., after being reflected, etc. 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 in which multiple signals that have traveled multiple different paths are combined.

The receiving side detects, as the first arriving wave, a signal that satisfies a predetermined detection criterion among the wireless signals received from the transmitting side. One example of the predetermined detection criterion is that the power value of the CIR exceeds a predetermined threshold for the first time. That is, the receiving side may detect, as the first arriving wave, a pulse corresponding to a portion of the CIR whose power value exceeds a predetermined threshold for the first time. Another example of the predetermined detection criterion is that the received power value of the received wireless signal (i.e., the sum of the squares of the I and Q components of the received signal) exceeds a predetermined threshold for the first time. That is, the receiving side may detect, as the first arriving wave, a signal whose received power value exceeds a predetermined threshold for the first time among the received signals.

It should be noted here that the signal detected as the first arriving wave is not necessarily a direct wave. For example, if a direct wave is received in a state where it cancels out a delayed wave, the power value of the CIR may fall below a predetermined threshold, and the direct wave may not be detected as the first arriving wave. In that case, a delayed wave or a composite wave that arrives later than the direct wave may be detected as the first arriving wave.

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 from when a signal is transmitted to when it is received.

Here, one of the multiple wireless communication units 210 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 the master below. 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.

In the distance measurement process, multiple distance measurement signals can be transmitted and received between the communication unit 200 and the portable device 100. Of the multiple distance measurement signals, a distance measurement signal transmitted from one device to the other device is also referred to as a first distance measurement signal. Next, a distance measurement signal transmitted from a device that receives the first distance measurement signal to a device that transmitted the first distance measurement signal as a response to the first distance measurement signal is also referred to as a second distance measurement signal. Next, a distance measurement signal transmitted from a device that receives the second distance measurement signal to a device that transmitted the second distance measurement signal as a response to the second distance measurement signal is also referred to as a third distance measurement signal.

An example of the flow of the distance measurement process is described below with reference to Figure 7.

Figure 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.

As shown in FIG. 7, first, the portable device 100 transmits a first ranging signal (step S102). When the first ranging signal is received by the wireless communication unit 210A, the control unit 230 calculates the CIR of the first ranging signal. Then, the control unit 230 detects the first arriving wave of the first ranging signal in the wireless communication unit 210A based on the calculated CIR (step S104).

Next, the wireless communication unit 210A transmits a second ranging signal in response to the first ranging signal (step S106). When the portable device 100 receives the second ranging signal, it calculates the CIR of the second ranging signal. Thereafter, the portable device 100 detects the first arriving wave of the second ranging signal based on the calculated CIR (step S108).

Next, the portable device 100 transmits a third ranging signal in response to the second ranging signal (step S110). When the third ranging signal is received by the wireless communication unit 210A, the control unit 230 calculates the CIR of the third ranging signal. Thereafter, the control unit 230 detects the first arriving wave of the third ranging signal in the wireless communication unit 210A based on the calculated CIR (step S112).

The portable device 100 measures a time INT ₁ from the transmission time of the first ranging signal to the reception time of the second ranging signal, and a time INT ₂ 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 INT ₁ and INT ₂ (step S114). Such a signal is received, for example, by the wireless communication unit 210A.

The control unit 230 measures a time INT ₃ from the reception time of the first ranging signal to the transmission time of the second ranging signal, and a time INT ₄ 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.

Then, the control unit 230 estimates the distance R based on the times INT ₁ , INT ₂ , INT ₃ , and INT ₄ (step S116). For example, the control unit 230 estimates the propagation delay time τ _m by the following equation.

Thereafter, the control unit 230 estimates the distance R by multiplying the estimated propagation delay time τ _m by the speed of the signal.

- One cause of the decrease in estimation accuracy The reception times of the ranging signal, which are the start and end times of the times INT ₁ , INT ₂ , INT ₃ , and INT ₄ , are the reception times of the first arriving wave of the ranging signal. As described above, the signal detected as the first arriving wave is not necessarily a direct wave.

When a delayed wave or a composite wave arriving later than a direct wave is detected as the first arriving wave, the reception time of the first arriving wave is delayed compared to when a direct wave is detected as the first arriving wave. In this case, the estimated result of the propagation delay time τ _m varies from the true value (the estimated result when a direct wave is detected as the first arriving wave). The ranging accuracy decreases by the amount of the variation.

- Supplementary Note: 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 is highest in the portion of the CIR corresponding to the first arriving wave, or the time when the received power value of the first arriving wave is highest) as the reception time of the first arriving wave.

(2) Angle Estimation The communication unit 200 performs an angle estimation process. The angle estimation process is a process for estimating the angles α and β shown in FIG. 3. The angle acquisition process includes receiving an angle estimation signal and calculating the 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 process. An example of the flow of the angle estimation process will be described below with reference to FIG. 8.

Figure 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. This sequence involves the portable device 100 and the communication unit 200.

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-210D, the control unit 230 calculates the CIR of the angle estimation signal received by each of the wireless communication units 210A-210D. After that, the control unit 230 detects the first incoming wave of the angle estimation signal based on the calculated CIR for each of the wireless communication units 210A-210D (steps S204A-S204D). Next, the control unit 230 detects the phase of the detected first incoming wave for each of the wireless communication units 210A-210D (steps S206A-S206D). Then, the control unit 230 estimates the angles α and β based on the phase of the first incoming wave detected for each of the wireless communication units 210A-210D (step S208).

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 wireless signal at the time the first arriving wave is received.

The process in step S208 will be described in detail below. The phase of the first arriving wave detected for the wireless communication unit 210A is set as P _A. The phase of the first arriving wave detected for the wireless communication unit 210B is set as P _B. The phase of the first arriving wave detected for the wireless communication unit 210C is set as P _C. The phase of the first arriving wave detected for the wireless communication unit 210D is set as P _D. In this case, the antenna array phase differences Pd _AC and Pd _BD in the X-axis direction and the antenna array phase differences Pd _BA and Pd _DC in the Y-axis direction are respectively expressed by the following equations.

The angles α and β are calculated by the following formula, where λ is the wavelength of the radio wave and d is the distance between the antennas 211.

Therefore, the angles calculated based on the phase difference of each antenna array are expressed by the following equations:

The control unit 230 calculates the angles α and β based on the calculated angles 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 equation.

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.

In other words, a delayed wave or a composite wave may be detected as the first arriving wave. Typically, the phase of the delayed wave and the composite wave differs from the phase of the direct wave, and the angle estimation accuracy decreases by the amount of the difference.

- Supplementary Note: 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.

(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 following first and second calculation methods can be adopted as the coordinate estimation process.

- First Calculation Method The first calculation method is a method for 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 according to the following equations.

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

The control unit 230 uses the above relationship to calculate the coordinate z using the following formula:

-Second Calculation Method The second calculation method is a method for 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).

By rearranging equation (12) with respect to cos α and substituting it into equation (9), we obtain the coordinate x as follows:

By rearranging equation (13) with respect to cosβ and substituting it into equation (10), we obtain the coordinate y as follows:

Then, by substituting formula (14) and formula (15) into formula (11) and rearranging, we obtain the coordinate z as follows:

The above describes 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 with 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.

As described above, the coordinates are calculated based on the propagation delay time and the phase. These are both estimated based on the first arriving wave. Therefore, the coordinate estimation accuracy may decrease for the same reason as the ranging process and the angle estimation process.

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

In addition, as a process specific to the vehicle 202, the control unit 230 may estimate the area in which the portable device 100 is located from among multiple areas including the inside and outside of the vehicle 202. This makes it possible to provide detailed services, such as providing different services when the user is inside the vehicle and when the user is outside the vehicle. In addition, the control unit 230 may identify the area in which the portable device 100 is located from among a surrounding area, which is an area within a predetermined distance from the vehicle 202, and a distant area, which is an area that is a predetermined distance or more from the vehicle 202.

(5) Use of Estimation Results of Location Parameters The estimation results of the location parameters may be used, for example, for authenticating the portable device 100. For example, when the portable device 100 is present in an area close to the communication unit 200 on the driver's seat side, the control unit 230 determines that the authentication has been successful and unlocks the door.

<<3. Technical issues >>
The technical problem of this embodiment will be described with reference to Fig. 9 to Fig. 12. Fig. 9 to Fig. 12 are graphs for explaining the technical problem of this embodiment. The horizontal axis represents delay time. The vertical axis indicates the chip length, and the vertical axis indicates the absolute value of the CIR value (e.g., power value). The chip length is the time width per pulse. For example, when a pulse is created with a bandwidth of 500 MHz, The pulse width of about 2 ns is the chip length.

9 shows the CIR when a signal arrives via a fast path at a delay time of 1T _C , and a signal arrives via a path other than the fast path at a delay time of 3T _C. Referring to FIG. 9, peaks appear in the CIR waveform at both delay times of 1T _C and 3T _C. This shows that the CIR waveform adequately separates two multipath waves with a delay time of 2T _C apart.

FIG. 10 shows the CIR when a signal arrives via a fast path at a delay time of 1T _C and a signal arrives via a path other than the fast path at a delay time of 2T _C. The first signal arriving at a delay time of 1T _C and the second signal arriving at a delay time of 2T _C are in phase. Referring to FIG. 10, a peak appears in the CIR waveform at a delay time of 1T _C , while no peak appears in the CIR waveform at a delay time of 2T _C. Furthermore, the signal arriving at a delay time of 1T _C and the signal arriving at a delay time of 2T _C are combined in phase and appear as one waveform. Therefore, it can be seen that it is difficult to separate two multipath waves with a delay time of 1T _C apart using a CIR waveform.

FIG. 11 shows the CIR when a signal arrives via a fast path at a delay time of 1.2T _C , and signals arrive via paths other than the fast path at delay times of 1.7T _C and 3.6T _C. The first signal arriving at a delay time of 1.2T _C and the second signal arriving at a delay time of 1.7T _C are in opposite phase. Referring to FIG. 11, peaks appear in the CIR waveform at delay times of 1.2T _C and 3.6T _C. On the other hand, a second peak appears near a delay time of 2.2T _C. This is far from the true delay time of 1.7T _C. Therefore, it can be seen that it is difficult to separate two multipath waves with a delay time of 0.5T _C apart using the CIR waveform.

As shown in Figures 10 and 11, if the difference in delay time between when two multipath waves arrive at the receiving side is short, the delay time at which a peak occurs in the CIR waveform may vary from the original delay time. Therefore, the delay time detected as the reception time of the first arriving wave may vary from the original delay time. In such a case, the ranging accuracy decreases by the amount of the variation.

12 shows a CIR waveform 23 in the case where a signal arrives via a fast path with a delay time of 1T _C and a signal arrives via a path other than the fast path with a delay time of 1.5T _C. CIR waveform 21 is a CIR waveform in the case where a signal arrives via a fast path with a delay time of 1T _C alone. CIR waveform 22 is a CIR waveform in the case where a signal arrives via a path other than the fast path with a delay time of 1.5T _C alone. Note that the first signal arriving with a delay time of 1T _C and the second signal arriving with a delay time of 2T _C are out of phase with each other by 90 degrees.

When the difference in delay time between when two multipath waves arrive at the receiving side is short, a delayed wave or a composite wave may be detected as the first arriving wave. In the example shown in FIG. 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 by the amount of difference.

As in the example shown in FIG. 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 delayed wave. Therefore, if angle estimation is performed based on the phase at sampling point 31, the estimation accuracy will decrease.

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

Therefore, it would be desirable to be able to separate multipath waves with a higher resolution than CIR.

＜＜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 by a process described in detail below. In the following, as an example, a case where the subject that detects the first incoming wave is the communication unit 200 will be described. The process described below may be executed by the portable device 100.

(1) Formulation of Delay Profile First, the delay profile (i.e., CIR) in the PN (Pseudo-Noise) correlation method is formulated. The PN correlation method is a method of calculating the CIR by transmitting a signal consisting of a random sequence such as a PN sequence signal shared by the transmitting side and the receiving side, and taking a sliding correlation between the transmitted signal and the received signal. Note that the PN sequence signal is a signal in which 1s and 0s are arranged almost randomly.

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

In the following, it is assumed that the receiving antenna receives L multipath waves as signals corresponding to the transmission signal sent 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 passed through multiple paths are received by the receiving side.

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

Here, t is time. h _i is the complex response value of the i-th multipath wave. _{T 0i} is the propagation delay time of the i-th multipath wave. f is the frequency of the carrier wave of the transmission signal. v(t) is internal noise. Internal noise is noise generated inside the circuit on the receiver side.

For example, in the PN correlation method, the receiver shifts the time of a known transmitted signal u(t) and calculates the correlation with the received signal x(t), as shown in the following equation:

Note that u ^* () is the complex conjugate of u().

z(τ) is also called a delay profile. Also, |z(τ)| ² is also called a power delay profile. τ is the delay time.

The delay profile of the L-wave multipath wave is expressed by the following equation:

Here, r(τ) is the autocorrelation function of the PN sequence signal. The autocorrelation function is a function that calculates the correlation between a signal and the signal itself. r(τ) is given by the following formula.

Also, n(τ) is the internal noise component. n(τ) is given by the following formula:

(2) Sparse Reconstruction The number of samples of the received signal is M (where M>L). The received signal is sampled at M discrete delay times τ ₁ , τ ₂ , ..., τ _M. Note that 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. A data vector z consisting of M delay profiles is expressed by the following equation. Note that the following equation applies when the receiving side receives only one preamble symbol.

When L-wave multipath waves are received, the data vector z is expressed as follows:

Note that r(τ) is called the mode vector.

Furthermore, when the data vector z is expressed in matrix notation, it can be expressed as follows:

Here, _A0 is also called the mode matrix.

S ₀ is also referred to as the signal vector.

In sparse reconstruction, the data vector z is transformed into a form that involves the matrix product of A and s.

T ₁ , T ₂ , ..., T _N represent N delay times to be searched. T ₁ , T ₂ , ..., T _N are also called delay time bins. A delay time bin is an example of a set time. Note that N>>L.

Here, A is also referred to as an extended mode matrix. The extended mode matrix is a matrix of elements that represent delay profiles when a signal is assumed to be received at each of a number of delay time bins. For example, an element r(T ₁ ) of the extended mode matrix A is the delay profile of a signal when the signal is assumed to be received at time T ₁ .

s is also called the extended signal vector. The extended signal vector is a vector consisting of multiple elements that represent the presence or absence of a signal for each delay time bin, as well as the amplitude and phase of the signal.

(3) Estimation of Propagation Delay Time Based on Extended Signal Vector According to the 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 with N unknowns and M condition numbers (M<N). The control unit 230 estimates the reception time of the first arriving wave based on the delay time bins corresponding to multiple elements in the extended signal vector s.

Here, a non-zero element in the extended signal vector indicates that a signal is present in the delay time bin corresponding to the non-zero element. On the other hand, a zero element in the extended signal vector indicates that a signal is not present 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 multiple elements in the extended signal vector s as the reception time of the first arriving wave.

At this time, 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. The sparse solution is a vector in which only a predetermined number of elements are non-zero. The predetermined number is the number of pulses included in the received signal, which corresponds to one pulse included in the transmitted signal. In other words, the sparse solution is a vector in which only L elements are non-zero and the other elements are zero when L multipath waves are received. For example, when _s2 is non-zero among s=[ _s1 , _s2 , ..., _sN ], it is determined that a signal is received at delay time _T2 .

In particular, the control unit 230 estimates the earliest delay time bin among delay time bins corresponding to non-zero elements among elements included in the extended signal vector s as the reception time of the first arriving wave. For example, when _s2 , _s4 , and _s6 of s = [ _s1 , _s2 , ..., _sN ] are non-zero, it is determined that a signal via the fast path is received at delay time _T2 , and signals via paths other than the fast path are received at delay times _T4 and _T6 .

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 setting the number of N large in the sparse reconstruction, it becomes possible to separate the multipath waves with a resolution finer than the CIR. Therefore, in this embodiment, the number of delay time bins N is set larger than the number of samplings M of the received signal. In other words, in this embodiment, the time interval of N delay time bins T ₁ , T ₂ , ..., T _N is shorter than the time interval of M discrete delay times τ ₁ , τ ₂ , ..., τ _M. With this configuration, it becomes possible to separate the multipath waves with a resolution finer than the sampling interval of the received signal. As a result, it becomes possible to obtain the reception time of the first arriving wave with a resolution finer than the CIR.

(3) Compressive Sensing Algorithm The control unit 230 uses a compressive sensing algorithm to estimate an extended signal vector s that is a sparse solution. The compressive sensing algorithm is an algorithm that assumes that an unknown vector is a sparse vector and estimates an 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 refers to obtaining a result of multiplying an 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.

Examples of the compressed sensing algorithm include FOCUSS (Focal Underdetermined System Solver), ISTA (Iterative Shrinkage Thresholding Algorithm), and FISTA (Fast ISTA). The control unit 230 may employ any of these compressed sensing algorithms. In the following, an example of estimating an extended signal vector s using FOCUSS will be described. FOCUSS is an algorithm that assumes an initial value for an unknown vector and iteratively estimates the unknown vector using a general inverse matrix and a weighting matrix. FOCUSS can accurately estimate an unknown vector with a small number of iterations by using a general inverse matrix and a weighting matrix. The basic principles of FOCUSS are explained in detail in the non-patent literature "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."

The problem of estimating an extended signal vector s that provides a sparse solution from a delay profile z is an underdetermined problem with N unknowns and M conditions (note that M<N). Therefore, a solution is sought by adding another condition. Typically, a minimum norm solution is found by adding a condition that minimizes the norm of the extended signal vector s. Note that the norm is the length of the vector.

Determination of Initial Value s ₀ of -FOCUSS In the above formula (29), if internal noise n is ignored, multiplying the delay profile z by the inverse matrix of the extended mode matrix A eliminates matrix A (i.e., it becomes a unit matrix), so that the extended mode signal vector s can be extracted. However, the inverse matrix of the extended mode matrix A does not exist. Therefore, the minimum norm solution s _mn is found by multiplying the delay profile z by the generalized inverse matrix of the extended mode matrix A as shown in the following formula. The generalized inverse matrix may be a Moore-Penrose generalized inverse matrix.

Here, A ^{1 −} is the generalized inverse matrix of the extension mode matrix A. The generalized inverse matrix A 1 ⁻ of the extension mode matrix A is expressed by the following equation.

Since the extended mode matrix A does not disappear completely even when the extended mode matrix A is multiplied by the generalized inverse matrix A ⁻ of the extended mode matrix A, a vector similar to the extended signal vector s, which is a sparse solution, is calculated as the minimum norm solution s _mn . Note that the minimum norm solution s _mn becomes the initial value s ₀ of FOUCSS.

- Application of FOCUSS The minimum norm solution s _mn is not a sparse solution. Therefore, the control unit 230 estimates a sparse solution of the extended signal vector s, and estimates a weighted minimum norm solution, which is a vector that minimizes the norm of a vector obtained by weighting the extended signal vector s. By estimating the weighted minimum norm solution, it becomes possible to estimate a sparse solution. The weighted minimum norm solution is expressed by the following equation.

Where, W is a weighting matrix. The weighting matrix W is typically a diagonal matrix. That is, the problem of finding a weighted minimum norm solution for the augmented signal vector s is written as follows:

Specifically, the control unit 230 estimates the weighted minimum norm solution of the extended signal vector s by iteratively calculating the formulas (36), (37), and (38) shown in STEPs 1 to 3 below.

Here, k is the number of iterations. s _k is a candidate for the weighted minimum norm solution. (AW _K ) ⁻ is the generalized inverse matrix of AW _k . As explained above, the initial value of s _k is given as the minimum norm solution s _mn by the following equation.

The control unit 230 repeatedly executes the above STEP 1 to STEP 3. As one example, STEP 1 to STEP 3 may be repeatedly executed until s _k converges. As another example, STEP 1 to STEP 3 may be repeatedly executed a predetermined number of times. This makes it possible to estimate the extended signal vector s as a weighted minimum norm solution that is closer to the true value. This point will be described below.

Using the above formula (37), formula (38) is transformed into the following formula:

If we ignore the noise n in equation (29), equation (40) transforms to the following equation:

Here, if W _k (AW _k ) ^-A is a matrix that does not change s, such as a unit matrix, then s _k will be equal to s. In FOCUSS, by iteratively updating the weighting matrix W _k and bringing W _k (AW _k ) ^-A closer to a matrix that does not change s, such as a unit matrix, it becomes possible to estimate the extended signal vector s as a weighted minimum norm solution that is closer to the true value.

(4) Singular Value Decomposition When estimating the extended signal vector s, the control unit 230 may obtain a generalized inverse matrix (AW _k ) ⁻ of AW _k by performing singular value decomposition. In this case, the control unit 230 may obtain (AW _k ) ⁻ by using, for example, TSVD (Truncated Singular Value Decomposition).

In this case, the control unit 230 performs singular value decomposition of AW _k in equation (37) in STEP 2 above into a format including a diagonal matrix made up of singular values larger than a predetermined threshold, and then calculates (AW _k ) ⁻ . AW _k is subjected to singular value decomposition as shown in the following equation.

Here, S _t is a diagonal matrix consisting of t non-zero singular values. U _t is a matrix consisting of t columns of left singular vectors corresponding to S _t . V _t is a matrix consisting of t columns of right singular vectors corresponding to S _t . t is the number of dimensions of the signal subspace. The signal subspace is a space consisting of signals whose power is higher than a threshold. Note that V _t ^H is the complex conjugate transpose of the matrix V _t , and is also called the adjoint matrix of V _t . In this case, (AW _k ) ⁻ can be obtained by the following equation.

Here, S _t includes non-zero singular values of the number of dimensions t of the signal subspace. That is, S _t is a diagonal matrix consisting of t singular values whose values are greater than a predetermined threshold. And t is equal to the number L of multipath waves. Therefore, by calculating the general inverse matrix using only 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 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 general inverse matrix even under the influence of noise.

(5) Regularization In the above, the control unit 230 has been described as performing singular value decomposition to obtain (AW _k ) ⁻ . On the other hand, the control unit 230 may perform regularization using R-FOCUSS (Regularized-FOCUSS) or the like to obtain (AW _k ) ⁻ . In this case, the control unit 230 may use the following formula (44) instead of formula (37) in STEP 2 above. Note that A _k ^H is the complex conjugate transpose of the matrix A _k , and is also called the adjoint matrix of A _k .

However, if A _k A _k ^H is not regular in the above formula (44), the inverse matrix (A _k A _k ^H ) ⁻¹ cannot be obtained. Therefore, in STEP 2 above, the control unit 230 may use the following formula (45) instead of formula (44).

Here, α in Equation (45) 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 (45) above, even if A _k A _k ^H is not regular, it is possible to obtain the inverse matrix (A _k A _k ^H ) ⁻¹ of A _k A _k ^H by making A _k A _k ^H +αI regular. In addition, by using the regularization parameter, it is possible to more easily realize the convergence of S _k . The regularization parameter in FOCUSS is mentioned in the above-mentioned non-patent document.

The control unit 230 may use TSVD to obtain the inverse matrix (A _k A _k ^H ) ⁻¹ of A _k A _k ^H. In this case, the control unit 230 performs singular value decomposition on A _k A _k ^H in the above formula (44) into a format including a diagonal matrix made up of singular values larger than the first threshold value, and then calculates (A _k A _k ^H ) ⁻¹ . A _k A _k ^H is singular value decomposed as shown in the following formula.

In this case, (A _k A _k ^H ) ⁻¹ can be calculated by the following formula.

In addition, since A _m A _m ^H is a square matrix, the singular value decomposition here is also called eigenvalue decomposition, and TSVD is called TEVD (Truncated Eigen Value Decomposition).

A specific example of the calculation of (AW _k ) ⁻ has been described above. When differential value decomposition is used in the calculation of (AW _k ) ⁻ , unnecessary singular values can be removed, and the calculation time can be shortened in some cases. On the other hand, when differential value decomposition is used in the calculation of (AW _k ) ⁻ , the effect of improving the estimation accuracy is expected by not removing singular values.

(6) Threshold Processing In FOCUSS, threshold processing may be performed. The threshold processing here refers to a process of setting elements equal to or less than a predetermined threshold to 0. For example, the control unit 230 may set elements equal to or less than a predetermined threshold among elements included in the weighting matrix W _k in equation (36) in STEP 1 above to zero. As an example, threshold processing shown in the following equation may be performed in STEP 1 above.

Here, w _k (i) is the i-th diagonal element of the weight matrix W _k . s _k-1 (i) is the i-th element of the extended signal vector s _k-1 . |s _k-1 (i)| _max is the maximum value of the magnitude of the elements included in s _k-1 (i). ^{10 −5} |s _k-1 (i)| _max is an example of a threshold value.

According to the above threshold processing, when creating the weight matrix Wk, among the elements of the extended signal vector s, elements that have values less than the threshold are considered to be noise rather than a signal, and are converted to zero. This allows the extended signal vector s to converge more quickly. In addition, since the non-zero elements are reduced, it becomes easier to obtain a sparse solution.

(7) Simulation Results The present inventors performed a simulation with the settings shown in Table 1 below. Note that T _C is the chip length. Note that the simulation results shown here are for the case where (AW _k ) ⁻ was obtained using singular value decomposition in STEP 2 above.

The simulation results in the above settings will be described with reference to Fig. 13. Fig. 13 is a graph for explaining the simulation results 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 (e.g., power value) or the absolute value of the signal vector (e.g., power value). Fig. 13 shows a waveform 41 indicating a delay profile based on the PN correlation method, a waveform 42 indicating the minimum norm solution s _mn , and a waveform 43 indicating the extended signal vector s obtained by FOCUSS.

Referring to the waveform 43 showing the extended signal vector s, peaks are observed near delay times _1.2T , _1.7T , and _3.5T . The delay times at which these peaks are observed are almost the same as the delay times _1.2T , _1.7T , and _3.6T in the simulation settings. This shows that FOCUSS can correctly separate and detect multipath waves.

On the other hand, referring to the waveform 41 showing the delay profile based on the PN correlation method, a second peak appears near a delay time of 2.2T _C. This is significantly different from the second delay time of 1.7T _C in the simulation settings. Therefore, it is understood that it is difficult to correctly separate and detect multipath waves before applying FOCUSS. The cause of this is thought to be interference between a signal arriving via a fast path and a signal arriving via a path other than the fast path.

4.2. Estimation of location parameters
The control unit 230 estimates the position parameters based on the first arriving wave detected by the above-described process.

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 of estimating the distance R is as described above with reference to FIG.

However, the portable device 100 calculates the CIR for the second ranging signal, and performs sparse reconstruction and FOCUSS. The portable device 100 measures the time INT1 by taking the time corresponding to the earliest delay time bin among the delay time bins corresponding to the non-zero elements among the elements included in the extended signal vector s as the reception time of the first arriving wave of the second ranging signal. For example, when _s2 , _s4 , and _s6 of s=[ _s1 , _s2 , ..., _sN ] are non-zero, the time _INT1 is measured by taking the time corresponding to the delay time _T2 as the reception time of the first arriving _wave .

On the other hand, the communication unit 200 calculates the CIR for the first ranging signal, and performs sparse reconstruction and FOCUSS. Then, the communication unit 200 measures a time INT 3 by taking the time corresponding to the earliest delay time bin among delay time bins corresponding to non- _zero elements among elements included in the extended signal vector s as the reception time of the first arriving wave of the first ranging signal. Similarly, the communication unit 200 calculates the CIR for the third ranging signal, and performs sparse reconstruction and FOCUSS. Then, the communication unit 200 measures a time INT 4 by taking the time corresponding to the earliest delay time bin among delay time bins corresponding to non-zero elements among elements included in the extended signal vector s as the reception time of the first arriving wave of the _third ranging signal.

Then, the control unit 230 estimates the propagation delay time based on the times _T1 to _T4 , and estimates the distance R. As described above, since it is possible to search for the reception time of the first arriving wave with a finer resolution than the CIR, it is possible to improve the distance measurement accuracy accordingly.

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

More specifically, the control unit 230 estimates the angles α and β based on the phase of an element whose corresponding delay time bin is the earliest among one or more non-zero elements included in the extended signal vector s. For example, when _s2 , _s4 , and _s6 are non-zero among s = [ _s1 , _s2 , ..., _sN ], the control unit 230 estimates the angles α and β based on the phase of _s2 .

As explained above, multipath waves can be separated with a finer resolution than CIR. Therefore, by performing angle estimation based on the phase of the element of the extended signal vector s that corresponds to the reception time of the first arriving wave, it is possible to improve the accuracy of angle estimation.

<4.3. Processing flow>
FIG. 14 is a flowchart showing an example of the flow of a position parameter estimation process executed by the communication unit 200 according to this embodiment.

As shown in FIG. 14, first, the control unit 230 calculates a delay profile using the PN correlation method (step S302). Next, the control unit 230 converts the delay profile into a format including a matrix product of an extended mode matrix and an extended signal vector using sparse reconstruction (step S304). Next, the control unit 230 estimates an extended signal vector that is a weighted minimum norm solution using FOCUSS (step S306). Then, the control unit 230 estimates position parameters based on the estimated extended signal vector (step S308).

<4.4. Applicability of 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.

FOCUSS may be applied to the accumulated CIR obtained by accumulating the CIR for each preamble symbol. That is, the control unit 230 may convert the CIR into a format including a matrix product of the extended mode matrix and the extended signal vector, and may convert the accumulated CIR obtained by accumulating the CIR for each preamble symbol into a format including a matrix product of the extended mode matrix and the extended signal vector. Then, a sparse solution of the extended signal vector s is estimated by FOCUSS, and the reception time of the first arriving wave is estimated.

On the other hand, FOCUSS may be applied to the CIR for each preamble symbol. In that case, the final extended signal vector s may be estimated by accumulating the extended signal vector s estimated for each preamble symbol. That is, the control unit 230 may estimate the reception time of the first arriving wave based on the extended signal vector s, and may estimate the reception time of the first arriving wave based on the extended signal vector s after accumulation, which is the result of accumulating the extended signal vector s for each of the CIRs for multiple preambles.

The CIR may be calculated for each pulse. In that case, FOCUSS may be applied to the accumulated CIR obtained by accumulating the CIR for each pulse, or may be applied to the CIR for each pulse.

The CIR may also be calculated for the entire preamble. In that case, FOCUSS may be applied to the CIR calculated for the entire preamble.

Either method can produce similar results.

<4.5. Scope of FOCUSS>
FOCUSS may be applied to the entire CIR. For example, in the simulation setup shown in Table 1, FOCUSS may be applied to delay time bins 0 to _5TC .

On the other hand, FOCUSS may be applied to a part of the CIR. More specifically, FOCUSS may be applied to a vector (hereinafter also referred to as a partial vector) consisting of elements corresponding to some of the set times among the elements for each of the multiple set times included in the extended signal vector s. In this case, the control unit 230 estimates a sparse solution of the partial vector by estimating a sparse solution of the extended signal vector s. In other words, the control unit 230 estimates a weighted minimum norm solution, which is a vector that minimizes the norm of a vector obtained by weighting the partial vector. This makes it possible to reduce the calculation load compared to when FOCUSS is applied to the entire CIR.

In particular, if the purpose is to detect the first arriving wave, it is desirable to apply FOCUSS to a limited portion of the CIR near the reception time of the first arriving wave. In that case, FOCUSS is applied to a partial vector consisting of elements corresponding to the set times near the reception time of the first arriving wave, among the elements for each of the multiple set times included in the extended signal vector s. When calculating the CIR based on the preamble symbol, strong correlation is obtained only at the delay time where the pulse sequence of the transmitted signal and the pulse sequence of the received signal completely match, and correlation is low in other parts. Therefore, even if FOCUSS is applied to a limited portion of the CIR near the reception time of the first arriving wave, the detection accuracy of the first arriving wave can be maintained.

For example, in the simulation settings shown in Table 1, FOCUSS may be applied with delay time bins of 0 to 2T _C. The simulation results in this case are shown in FIG.

Fig. 15 is a graph for explaining the simulation results of this embodiment. Fig. 15 shows a waveform 41 showing a delay profile based on the PN correlation method, a waveform 42 showing the minimum norm solution s _mn , and a waveform 43 showing the extended signal vector s obtained by FOCUSS. The waveform 42 showing the minimum norm solution s _mn and the waveform 43 showing the extended signal vector s are plotted from 0 to 2T _C , but are not plotted after 2T _C. In other words, it can be seen that the calculation load is reduced because calculations are omitted after 2T _C.

Referring to the waveform 43 showing the extended signal vector s, peaks appear near delay times 1.2T _C and 1.7T _C. The delay times at which these peaks appear are almost the same as the delay times 1.2T _C and 1.7T _C in the simulation settings. Therefore, it can be seen that even if the application range of FOCUSS is limited, it is possible to correctly separate and detect multipath waves within the application range.

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

4.6. Modifications
In the above embodiment, an example has been described in which the norm is a so-called l0 norm. The l0 norm refers to a case in which the multiplier p in the lp norm is 0. The lp norm is defined by the following equation.

On the other hand, the l0 norm is defined by the following equation, where p = 0 in the above equation (49):

However, in formula (50), it is assumed that 0 ⁰ =0.

That is, the l0 norm is the number of nonzero components in a vector.

The method of repeatedly executing formulas (36) to (38) described in the above embodiment is a method of minimizing the l0 norm as a weighted minimum norm solution of the extended vector s. In contrast, the control unit 230 may minimize the lp norm as a weighted minimum norm solution of the extended vector s. Specifically, the control unit 230 may use the following formula instead of STEP 1 above.

Here, p is a constant between 0 and 1. When p is 0, the above formula (51) is the same as formula (36). That is, the control unit 230 may estimate the weighted minimum norm solution by setting p to 0 in the above formula (51).

Even if p is a value other than 0, it is possible to accurately estimate the reception time of the first arriving wave, as in the above embodiment.

<<5. Supplementary Information>>
Although the preferred embodiment of the present invention has been described in detail above with reference to the accompanying drawings, the present invention is not limited to such an example. It is clear that a person having ordinary knowledge in the technical field to which the present invention pertains can conceive of various modified or altered examples within the scope of the technical ideas described in the claims, and it is understood that these also naturally belong to the technical scope of the present invention.

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 executed 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 received signal received by each of them. Furthermore, the estimation of the location parameters may be executed by the wireless communication unit 210 functioning as the master, for example.

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 in an antenna pair, but the present invention is not limited to such an example. As an example, the communication unit 200 may calculate angles α and β by performing beamforming using multiple antennas 211. In that case, the communication unit 200 scans the main lobes of the multiple antennas 211 in all directions, determines that the portable device 100 is located in the direction with the strongest received power, and calculates angles α and β based on that direction.

For example, in the above embodiment, as explained with reference to FIG. 3, the local coordinate system has been 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. In addition, 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.

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.

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 is applicable to any system that estimates location parameters and performs authentication by transmitting and receiving signals. For example, the present invention is applicable to a pair including any two devices from among a mobile device, a vehicle, a smartphone, a drone, a house, and a home appliance. In this case, one of the pair acts as an authenticator and the other acts as an authenticatee. Note that the pair may include two devices of the same type, or may include two different types of devices. The present invention is also applicable to a wireless LAN (Local Area Network) router identifying the location of a smartphone.

For example, in the above embodiment, the wireless communication standard is UWB, but the present invention is not limited to this example. For example, the wireless communication standard may be infrared.

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, in a recording medium (non-transitory media) provided inside or outside each device. Each program is then loaded into RAM, for example, when executed by a computer, and executed by a processor such as a CPU. The recording medium is, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, etc. The computer programs may also be distributed, for example, via a network, without using a recording medium.

In addition, the processes described in this specification using flowcharts do not necessarily have to be performed in the order shown. Some processing steps may be performed in parallel. Also, additional processing steps may be employed, and some processing steps may be omitted.

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

Claims (18)

a wireless communication unit that wirelessly receives signals from other communication devices;
a correlation between a second signal, which is a signal corresponding to the first signal received by the wireless communication unit when the other communication device transmits a signal including a pulse as a first signal, and the first signal is calculated at regular intervals;
converting a correlation calculation result, which is a result of taking a correlation between the second signal and the first signal for each of the specified times, into a format including a matrix product of 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, and an extended signal vector, which is a vector consisting of a plurality of elements representing the presence or absence of a signal for each of the set times, and the amplitude and phase of the signal;
a control unit that estimates a reception time of the second signal based on set times corresponding to the plurality of elements in the extended signal vector;
Equipped with
The set time interval is shorter than the specified time.
Communications equipment. The communication device according to claim 1, wherein the control unit estimates the set time corresponding to a non-zero element among the set times corresponding to the multiple elements in the extended signal vector as the reception time of the second signal. The control unit estimates a sparse solution of the extended signal vector, and estimates the set time corresponding to a non-zero element of the sparse solution of the estimated extended signal vector as a reception time of the second signal;
The sparse solution is a vector with only a predetermined number of elements being non-zero;
3. The communication device according to claim 2, wherein the predetermined number is a number of pulses contained in the second signal that correspond to one pulse contained in the first signal. The communication device according to claim 3, wherein the control unit estimates the earliest setting time among the setting times corresponding to non-zero elements in the sparse solution of the estimated extended signal vector as the reception time of the second signal. The communication device according to claim 3 or 4, wherein the control unit estimates the sparse solution of the extended signal vector by estimating a weighted minimum norm solution, which is a vector that minimizes the norm of a vector obtained by weighting the extended signal vector. The communication device according to claim 5 , wherein the control unit estimates the weighted minimum norm solution by iteratively calculating Equation (1), Equation (2), and Equation (3).

Here, k is the number of iterations. s _k is the weighted minimum norm solution candidate. p is a constant between 0 and 1. A is the extended mode matrix. (AW _K ) ⁻ is the generalized inverse matrix of AW _k . The initial value of s _k is given by the following equation.

where s _mn is the augmented signal vector that minimizes the norm of the augmented signal vector. The communication device according to claim 6, wherein the control unit estimates the weighted minimum norm solution by setting p to 0 in the formula (1). The communication device according to claim 6 or 7, wherein the control unit performs singular value decomposition of AW _k in the formula (2) into a form including a diagonal matrix composed of singular values having values greater than a predetermined threshold, and then calculates (AW _k ) ⁻ . The communication device according to claim 6 , wherein the control unit uses a formula (5) instead of the formula (2).

Here, A _k ^H is the adjoint matrix of A _k . The control unit uses formula (6) instead of formula (5).
10. The communication device of claim 9.

Here, α is a small positive quantity, and I is the identity matrix. The communication device according to claim 6, wherein the control unit sets elements of W _k in the formula (1) that are equal to or smaller than a predetermined threshold to zero. The communication device according to any one of claims 5 to 11, wherein the control unit estimates the sparse solution of the extended signal vector by estimating a weighted minimum norm solution, which is a vector that minimizes the norm of a vector obtained by weighting a vector consisting of elements corresponding to some of the set times among the elements for each of the multiple set times included in the extended signal vector. The communication device according to any one of claims 1 to 12, wherein the control unit estimates the distance between the communication device and the other communication device based on the estimated reception time of the second signal. The communication device according to any one of claims 1 to 13, wherein the control unit estimates an angle between a coordinate axis and a straight line connecting the origin of a coordinate system based on the communication device and the other communication device based on the phase of an element having the earliest corresponding setting time among one or more non-zero elements included in the extended signal vector. the other communication device transmits, as the first signal, a signal including a plurality of preamble symbols, the preamble symbols being a pulse sequence including one or more pulses;
The control unit converts the correlation calculation result into a format including a matrix product of the extension mode matrix and the extension signal vector, and converts a result of accumulating a plurality of correlation calculation results, which are the results of taking the correlation between each of the portions corresponding to the plurality of preamble symbols in the second signal and the preamble symbol at each specified time, into a format including a matrix product of the extension mode matrix and the extension signal vector. the other communication device transmits, as the first signal, a signal including a plurality of preamble symbols, the preamble symbols being a pulse sequence including one or more pulses;
The control unit estimates the reception time of the second signal based on the result of accumulating the extended signal vector for each of a plurality of correlation calculation results, which are the results of taking a correlation between each of the portions of the second signal corresponding to the plurality of preamble symbols and the preamble symbol at each specified time. wirelessly receiving a signal from another communication device;
calculating a correlation between a second signal, which is a signal corresponding to a first signal received when the other communication device transmits a signal including a pulse as a first signal, and the first signal at regular intervals;
converting a correlation calculation result, which is a result of taking a correlation between the second signal and the first signal for each of the specified times, into a format including a matrix product of 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, and an extended signal vector, which is a vector consisting of a plurality of elements representing the presence or absence of a signal for each of the set times, and the amplitude and phase of the signal;
estimating a time of receipt of the second signal based on set times corresponding to the elements in the extended signal vector;
Equipped with
The set time interval is shorter than the specified time.
Information processing methods. 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 second signal, which is a signal corresponding to the first signal and is received by a wireless communication unit that wirelessly receives a signal from the other communication device, at regular intervals;
converting a correlation calculation result, which is a result of taking a correlation between the second signal and the first signal for each of the specified times, into a format including a matrix product of 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, and an extended signal vector, which is a vector consisting of a plurality of elements representing the presence or absence of a signal for each of the set times, and the amplitude and phase of the signal;
a control unit that estimates a reception time of the second signal based on set times corresponding to the plurality of elements in the extended signal vector;
Function as a
The set time interval is shorter than the specified time.
program.

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