Positioning system, vehicle equipped with the same, and positioning method

Abstract

Provided are: a positioning system which can perform high-precision, high-resolution angle estimation of a target without using wires or cables among a plurality of transceivers or radars; a vehicle provided with the same; and a positioning method. A positioning system 1 is provided with a plurality of radars 21, 22, and a signal processing unit 3. The signal processing unit 3 acquires, from the radars 21, 22, a plurality of pieces of antenna data obtained by transmitting / receiving electromagnetic waves among a plurality of transmission antennas Tx and a plurality of reception antennas Rx. In a target angle estimation process using an AF method, a convolution matrix is generated by stacking the plurality of pieces of antenna data in the row direction of the matrix and synthesizing the result thereof, and calculating a filter coefficient vector from simultaneous equations expressed by using the product of this convolution matrix and a matrix of filter coefficient vectors. The inter-antenna phase difference is computed on the basis of the calculated filter coefficient vector, and computation for estimating the arrival angle of the wave reflected from the target is carried out on the basis of the computed inter-antenna phase difference.

Description

Technical Field

[0001] The present invention relates to a positioning system that includes a plurality of transceivers for positioning the position of a target, a vehicle equipped with the same, and a positioning method.

Background Art

[0002] Conventionally, as a system for positioning the position of a target using a plurality of transceivers, there is a millimeter-wave radar system disclosed in Non-Patent Document 1. In this millimeter-wave radar system, a master radar chip and a slave radar chip are cascade-connected, and each radar chip operates synchronously. The master radar chip and the slave radar chip share a millimeter-wave band signal generated by a PLL circuit inside the master radar chip via a wiring formed on a printed circuit board, thereby achieving phase synchronization. By achieving this phase synchronization, each radar chip performs a multi-static operation, and the positioning accuracy of the target is improved due to an increase in the antenna aperture length.

Prior Art Documents

Non-Patent Documents

[0003]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the above-described conventional positioning system, in order to achieve synchronization between a plurality of transceivers (radar chips), wiring through which a high-frequency signal in the millimeter-wave band (30 - 300 GHz) for connecting between the transceivers propagates is required. If each transceiver is formed in proximity on the same printed circuit board and the wiring is short, there is no problem even if a high-frequency signal in the millimeter-wave band propagates. However, when the distance between the transceivers is slightly increased, a special cable is required such that no loss or phase variation occurs even when a high-frequency signal in the millimeter-wave band propagates.

[0005] An object of the present invention is to provide a positioning system capable of performing highly accurate and high-resolution target angle estimation using a plurality of transceivers without using such wiring or cables, a vehicle including the same, and a positioning method.

Means for Solving the Problem

[0006] For this purpose, the present invention includes a plurality of transceivers each including a plurality of transmission antennas that transmit radio waves and a plurality of reception antennas that receive reflected waves from a target, and a signal processing unit that performs target angle estimation using an Annihilating Filter method (hereinafter referred to as the AF method) using a nulling filter and is configured such that the signal processing unit Obtained by a plurality of receiving antennas generates a convolution matrix by stacking and synthesizing a plurality of antenna data in the row direction of a matrix, obtains a filter coefficient vector from a system of simultaneous equations expressed using the product of the convolution matrix, with the filter coefficient vector being unknown, and the filter coefficient vector of the transfer function of the nulling filter, calculates the phase difference between antennas from the obtained filter coefficient vector, and performs an operation to estimate the arrival angle of the reflected wave from the target based on the calculated phase difference between antennas to configure a positioning system.

[0007] Further, the present invention Performing target angle estimation using the AF method with a nulling filter Positioning method In Stacking and synthesizing in the row direction of a matrix a plurality of antenna data obtained by a plurality of transmitting antennas that transmit radio waves and a plurality of receiving antennas that receive reflected waves from a target, each provided in a plurality of transceivers, to generate a convolution matrix; Obtaining a filter coefficient vector from a system of simultaneous equations expressed using the product of a convolution matrix, with the filter coefficient vector of the nulling filter being unknown, and the filter coefficient vector of the transfer function of the nulling filter; Calculating the phase difference between antennas from the obtained filter coefficient vector; Performing an operation to estimate the arrival angle of the reflected wave from the target based on the calculated phase difference between antennas A positioning method including the above is configured.

[0008] According to this configuration, by performing positioning of a target using a plurality of transceivers, a plurality of antenna data more than the antenna data obtained by a single transceiver can be obtained. In the target angle estimation process using the AF method, by stacking this plurality of antenna data in the row direction of the convolution matrix, a convolution matrix in which the plurality of antenna data are synthesized is generated. Therefore, the system of simultaneous equations expressed using the product of this convolution matrix and the filter coefficient vector has a larger number of equations than the system of simultaneous equations expressed using the convolution matrix of the antenna data obtained by a single transceiver. For this reason, the filter coefficient vector obtained by solving the system of simultaneous equations is accurately represented. Therefore, the phase difference between antennas of the receiving antenna is accurately calculated from the accurately represented filter coefficient vector. For this reason, by estimating the arrival angle of the reflected wave from the target using this phase difference between antennas, it is possible to perform high-precision and high-resolution target angle estimation using a plurality of transceivers.

[0009] Also, the present invention configures a vehicle including the positioning system described above.

[0010] According to this configuration, a vehicle can be equipped with a positioning system that can perform target angle estimation with high precision and high resolution using a plurality of transceivers.

Advantages of the Invention

[0011] As a result, according to the present invention, it is possible to provide a positioning system that can perform target angle estimation with high precision and high resolution using a plurality of transceivers without using wiring or cables, a vehicle equipped with the same, and a positioning method.

Brief Description of the Drawings

[0012]

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Mode for Carrying Out the Invention

[0013] Next, a mode for implementing the positioning system of the present invention and a vehicle equipped with the same will be described.

[0014] FIG. 1 is a block diagram showing a schematic configuration of a positioning system 1A according to a first embodiment of the present invention.

[0015] The positioning system 1A includes a first radar 21, a second radar 22, and a signal processing unit 3. The first radar 21 and the second radar 22 may also be collectively referred to as the radar 2.

[0016] The first radar 21 and the second radar 22 are each MIMO (Multiple-Input Multiple-Output) radars 2 operating in the FMCW (Frequency Modulated Continuous Wave) mode or the FCM (Fast-Chirp Modulation) mode, and constitute a plurality of transceivers with the same configuration. The first radar 21 and the second radar 22 are each provided as a transceiver 4. The transceiver 4 is provided with a plurality of transmit antennas Tx and a plurality of receive antennas Rx. The transmit antennas Tx and the receive antennas Rx are each formed at equal intervals.

[0017] The RF signal generated by the RF signal generation unit 5 is amplified by the power amplifier PA, becomes a transmission signal, and is transmitted from the transmit antenna Tx. The signal transmitted from the transmit antenna Tx becomes a radio wave and is reflected by the target. The reflected wave from the target is received by the receive antenna Rx. The reflected wave received by the receive antenna Rx is amplified by the low-noise amplifier LNA and output to the mixer 6. In the mixer 6, the transmission signal and the reception signal are mixed to generate an intermediate frequency signal (IF signal). The IF signal is converted into a digital signal by the ADC (Analog-to-Digital Converter) 7 and output to the signal processing unit 3.

[0018] As shown in the graph of Fig. 2(a), when the transmission signal Vtx transmitted from the transmit antenna Tx and the reception signal Vrx received by the receive antenna Rx are represented as chirp signals, the IF signal is represented as shown in the graph of Fig. 2(b). The horizontal axis of the graph in Fig. 2(a) is time [t], the vertical axis is the chirp frequency [GHz], the horizontal axis of the graph in Fig. 2(b) is time [t], and the vertical axis is the IF frequency [MHz].

[0019] In this case, as shown in the graph of Fig. 2(a), the chirp period of the IF signal sampled by ADC7 is Tm, the bandwidth of the chirp signal is BW, the lower frequency limit of the bandwidth BW is fmin, and the upper frequency limit is fmax. At this time, if the initial phase of the transmission signal Vtx is φ1, and the amplitudes of the transmission signal Vtx and the reception signal Vrx are Atx and Arx respectively, the transmission signal Vtx and the reception signal Vrx are expressed by the following equations (1) and (2).

Equation

[0020] N antennas (N is an integer of 2 or more) are virtually formed by the MIMO radar. The phase φangl(n) of the IF signal due to the arrival angle θ of the reflected wave at the n-th antenna among these N antennas, with the interval between the N antennas arranged at equal intervals being d, the chirp center frequency fc = fmin + BW / 2, the speed of light being c, and the distance to the target 11 being R as shown in Fig. 3, is expressed by the following equation (3). Note that Fig. 3 shows a positioning system 1A with M radars 2 (M is an integer of 2 or more).

Equation

[0021] The IF signal VIF(t,n) at time t obtained from the reception signal of the antenna with antenna number n is expressed by the following equation (4) using this equation (3).

Equation

[0022] The signal processing unit 3 is composed of a personal computer (PC), an electronic control unit (ECU) mounted on a vehicle, etc.

[0023] Before explaining the signal processing by the signal processing unit 3 in the positioning system 1A of this embodiment, an overview of the signal processing by the signal processing unit in a general positioning system will be explained using the flowchart shown in Fig. 4.

[0024] The signal processing unit acquires antenna data Y1 that is transmitted from the transmission antenna Tx of the first radar 21 and received by the reception antenna Rx of the first radar 21 (see FIG. 4, step 101).

[0025] Next, the signal processing unit performs FFT (Fast Fourier Transform) processing on the IF signal, and calculates the relative speed of the positioning system 1A with respect to the target 11 by using the Doppler frequency difference from the Doppler shifts of the transmission signal Vtx and the reception signal Vrx (see step 105). Next, the signal processing unit 3 calculates the distance R to the target 11 (see step 106). The calculation methods for the relative speed and the distance R may be general methods such as FFT, MUSIC method, ESPRIT method, etc.

[0026] For simplicity, assuming that the target 11 is a stationary object and the first-order partial derivative of the term (2Rfmin / c) representing the distance R in Equation (4) is 0 (speed = 0), the amplitude x(t, n) of the IF signal obtained from the reception signal of the antenna with antenna number n at time t is expressed by the following Equation (5) from Equation (4). The waveform of the reception signal is shown in the graph of FIG. 5(a). The horizontal axis of the graph represents the number of ADC samples by the ADC7, and the vertical axis represents the signal amplitude of the reception signal.

Equation

[0027] When the signal processing unit performs distance FFT processing on this reception signal, as shown in the graph of FIG. 5(b), the reception signal Xn(fpeak) is obtained at the peak frequency fpeak. The horizontal axis of the graph represents the frequency, and the vertical axis represents the reception power. The phase of this reception signal Xn(fpeak) is (ndsinθ / c)·fc as shown in Equation (5).

[0028] After calculating the relative speed and the distance R, the signal processing unit performs a CFAR (Constant False Alarm Rate) process to detect the peak of the IF signal (see step 107), and detects the target 11 as a target from among the background noise.

[0029] Next, the signal processing unit performs an angle estimation process of the target 11 using the AF method with a nulling filter. In this angle estimation process, the signal processing unit first generates a convolution matrix C from the antenna data Y1 acquired in step 101, and estimates the filter coefficient vector H of the transfer function of the nulling filter (see step 108).

[0030] Generally, assuming that the antenna data at the n-th antenna among N antennas is x shown in the following equation (6), and the antenna data Y1 acquired in step 101 is as shown in the following equation (6), the convolution matrix C is expressed by the following equation (7) with the estimated wave number being K.

Equation

[0031] The filter coefficient vector H has filter coefficients h0, h1,..., h in the transfer function h(z) of the nulling filter. k Then, it is expressed by the following equation (8). The estimation of the filter coefficient vector H is performed by solving a set of simultaneous equations in which the L2 norm of the matrix product of the convolution matrix C and the filter coefficient vector H with the filter coefficient vector H as an unknown is minimized, that is, by obtaining the filter coefficient vector H. Here, H T is the transposed filter coefficient vector H.

Equation

[0032] Next, the signal processing unit performs phase calculation using the polynomial equation shown in the following formula (10) from the obtained filter coefficient vector H (see step 109). In this phase calculation, the solution z=z of the polynomial equation with the transfer function h(z) set to 0 is used. k (where 1≦k≦K) is calculated.

number

[0033] This solution z k is the phase difference between the antennas w k Here, z k And w k There is a relationship between these as shown in the following equation (11).

number

[0034] Next, the signal processing unit calculates the arrival angle θ of the reflected wave from the kth target 11 from the above inter-antenna phase difference by the following equation (12). k (See step 110.) This angle θ k is the angle at which the positioning system 1A is positioned relative to the k-th target 11, as shown in FIG.

number

[0035] Next, an overview of signal processing by the signal processing unit 3 in the positioning system 1A of this embodiment will be described with reference to the flowchart shown in Fig. 6. Note that in this flowchart, processes that are the same as or equivalent to those in the flowchart shown in Fig. 4 will be described with the same reference numerals.

[0036] In the signal processing unit 3 of the positioning system 1A according to the present embodiment, first, antenna data Y1 transmitted from the transmission antenna Tx of the first radar 21 and received by the reception antenna Rx of the first radar 21 is acquired (see FIG. 6, step 101). Next, antenna data Y2 transmitted from the transmission antenna Tx of the second radar 22 and received by the reception antenna Rx of the second radar 22 is acquired (see step 104).

[0037] Next, the processes of steps 105 to 107 are performed in the same manner as the processes shown in the flowchart of FIG. 4 by a general signal processing unit. That is, in step 105, the signal processing unit 3 calculates the relative speed of the positioning system 1A with respect to the target 11 by using the Doppler frequency difference from the Doppler shifts of the transmission signal Vtx and the reception signal Vrx. Next, in step 106, the signal processing unit 3 calculates the distance R to the target 11. Next, in step 107, the signal processing unit 3 performs a CFAR process for detecting the peak of the IF signal.

[0038] Next, in step 108, the signal processing unit 3 stacks (accumulates) a plurality of antenna data Y1 and Y2 having different initial phases, which are acquired in steps 101 and 104, in the row direction of a matrix and synthesizes them to generate a convolution matrix C, and estimates a filter coefficient vector H of the transfer function of the nulling filter. At this time, the signal processing unit 3 estimates the wave number of the reflected wave arriving from the target 11 as K and performs calculations. In the AF method, in this way, when estimating the angle of the target 11, it is possible to stack the antenna data Y1 and Y2 having different initial phases into the convolution matrix C.

[0039] For example, it is assumed that antenna data Y1 and Y2 represented by the following equation (13) are obtained in steps 101 and 104.

Equation

[0040] In this case, as represented by the following equation (14), the convolution matrix C is each antenna data Y 11and Y2 are stacked in the row direction of the matrix to be generated.

Number

[0041] Using the matrix product of this convolution matrix C and the filter coefficient vector H, the system of linear equations represented by equation (9) has a larger number of equations than the system of linear equations represented using the convolution matrix C of the antenna data obtained by a single radar. Therefore, the filter coefficient vector H obtained by solving the system of linear equations is accurately represented. Thus, from the accurately represented filter coefficient vector H, the phase difference w k between antennas is accurately calculated. For this reason, in step 109 and step 110, using this phase difference w k between antennas, the arrival angle θ k of the reflected wave from the target 11 can be estimated, enabling high-precision and high-resolution angle estimation of the target using a plurality of transceivers.

[0042] In this way, in a general positioning system, the system of linear equations represented by equation (9) deteriorates in accuracy because the relationship between the estimated wave number K and the number of antennas N in equation (7) is an ill-determined problem when K > (N - 1) / 2. However, in the positioning system 1A according to the present embodiment, this condition is relaxed by stacking the antenna data in the row direction of multiple rows, improving the estimation accuracy. However, it is a condition that the target position does not change during the acquisition of each antenna data. Therefore, wiring and cables for phase synchronization are unnecessary.

[0043] Note that in FIG. 3, the antenna data acquired by each radar 21, 22,..., 2 M at a plurality of points (M points) are respectively grouped as Y1, Y2,..., Y M . Each antenna data Y1, Y2,..., Y M is represented by the following equation (15).

Number

[0044] According to the positioning system 1A according to such a first embodiment, by performing the positioning of the target 11 using a plurality of radars 21 and 22, a plurality of antenna data Y1 and Y2, which are more than the antenna data obtained by a single radar, are obtained. In the angle estimation process of the target 11 using the AF method in FIGS. 6 and steps 108 to 110, by stacking these plurality of antenna data Y1 and Y2 with different initial phases in the row direction of the convolution matrix C as in equation (14), a convolution matrix C in which a plurality of antenna data are combined is generated.

[0045] Therefore, in the simultaneous equations represented by equation (9) using the matrix product of this convolution matrix C and the filter coefficient vector H, the number of equations thereof is larger than the simultaneous equations represented using the convolution matrix C of the antenna data obtained by a single radar. For this reason, the filter coefficient vector H obtained by solving the simultaneous equations is accurately represented. Therefore, from the accurately represented filter coefficient vector H, the inter-antenna phase difference w k is accurately calculated.

[0046] For this reason, this inter-antenna phase difference w k is used to estimate the arrival angle θ k of the reflected wave from the target 11, so that it becomes possible to perform angle estimation of the target with high accuracy and high resolution using a plurality of transceivers. In this way, in a general positioning system, the simultaneous equations represented by equation (9) deteriorate in accuracy because the relationship between the estimated wave number K in equation (7) and the number of antennas N is an ill-determined problem when K > (N - 1) / 2. However, in the positioning system 1A according to the present embodiment, this condition is relaxed by stacking the antenna data in the row direction of a plurality of rows, and the estimation accuracy is improved. However, it is a condition that the target position does not change during the acquisition of each antenna data.

[0047] As a result, according to the positioning system 1A according to the first embodiment, without using wiring or cables, the arrival angle θ of the target 11 that can be made highly accurate and highly resolved using a plurality of transceivers kIt is possible to provide a positioning system 1A that can estimate an angle. Therefore, an additional circuit for high-frequency synchronization in the millimeter-wave band, which is conventional, becomes unnecessary, enabling the positioning system 1A to consume less power and also eliminating the need for wiring and cables, thus reducing the cost of the positioning system 1A.

[0048] Next, a positioning system according to a second embodiment of the present invention will be described. FIG. 7 is a block diagram showing a schematic configuration of a positioning system 1B according to the second embodiment. In FIG. 7, the same or corresponding parts as those in FIG. 1 are denoted by the same reference numerals and their description is omitted.

[0049] The positioning system 1B according to the second embodiment is different from the positioning system 1A according to the first embodiment in that it includes a low-frequency synchronization signal generation unit 8 that synchronizes signal processing in the frequency band of the IF signal obtained by mixing and calculating the transmission signal Vtx and the reception signal Vrx in each of the radars 21 and 22 among the radars 21 and 22. Other points are the same as those of the positioning system 1A according to the first embodiment.

[0050] The low-frequency synchronization signal generation unit 8 is connected to the low-frequency synchronization signal input terminal 4a of each transceiver 4 via a cable 9. The low-frequency synchronization signal generation unit 8 generates a low-frequency synchronization signal in the IF frequency band shown in the graph of FIG. 8(b) that is synchronized with the transmission signal Vtx shown in the graph of FIG. 8(a). In FIG. 8, the same or corresponding parts as those in FIG. 2 are denoted by the same reference numerals and their description is omitted. Also, the horizontal axis of the graph in FIG. 8(a) is time [t], the vertical axis is the chirp frequency, and the horizontal axis of the graph in FIG. 8(b) is time [t], and the vertical axis is the signal intensity.

[0051] The low-frequency synchronization signal output by the low-frequency synchronization signal generation unit 8 is supplied to each of the radars 21 and 22 via the low-frequency synchronization signal input terminal 4a of the transceiver 4 in each of the radars 21 and 22 through the cable 9. Each of the radars 21 and 22 operates in synchronization with the low-frequency synchronization signal.

[0052] FIG. 9 is a flowchart showing an outline of signal processing by the signal processing unit 3 in the positioning system 1B according to the second embodiment. In the same flowchart, for the processes that are the same as or corresponding to the flowchart shown in FIG. 6, the same reference numerals are given and the description thereof is omitted.

[0053] The positioning system 1B according to the second embodiment is different from the positioning system 1A according to the first embodiment in that radio waves are transmitted and received between a plurality of transmission antennas Tx and a plurality of reception antennas Rx included in a plurality of radars 21 and 22. Other points are the same as those of the positioning system 1A according to the first embodiment.

[0054] That is, in the signal processing by the signal processing unit 3 in the positioning system 1B according to the second embodiment, in FIGS. 9, steps 101 to 104, a plurality of antenna data Y1(1), Y2(1), Y1(2), Y2(2) are acquired. That is, the signal processing unit 3 acquires the antenna data Y1(1) transmitted from the transmission antenna Tx of the first radar 21 and received by the reception antenna Rx of the first radar 21 (see FIG. 9, step 101). Next, the antenna data Y2(1) transmitted from the transmission antenna Tx of the first radar 21 and received by the reception antenna Rx of the second radar 22 is acquired (see step 102). Next, the antenna data Y1(2) transmitted from the transmission antenna Tx of the second radar 22 and received by the reception antenna Rx of the first radar 21 is acquired (see step 103). Next, the antenna data Y2(2) transmitted from the transmission antenna Tx of the second radar 22 and received by the reception antenna Rx of the second radar 22 is acquired (see step 104).

[0055] For example, it is assumed that the antenna data Y1(1), Y1(2), Y2(1), Y2(2) represented by the following formula (16) are obtained in steps 101 to 104.

Equation

[0056] In this case, the convolution matrix C is generated by stacking each antenna data Y1(1), Y1(2), Y2(1), Y2(2) in the row direction of the matrix as expressed by the following equation (17).

Equation

[0057] FIG. 10 shows a positioning system 1B having M (M is an integer of 2 or more) radars 2, similar to FIG. 3. As shown in FIG. 10, in the positioning system 1B, each radar 21, 22,..., 2 M is supplied with a low-frequency synchronization signal from the low-frequency synchronization signal generation unit 8. In FIG. 10, the same reference numerals are assigned to the parts that are the same as or corresponding to those in FIGS. 3 and 7, and the description thereof is omitted.

[0058] In the positioning system 1B shown in FIG. 10, each radar 21, 22,..., 2 M performs mutual transmission and reception in addition to the operation of the positioning system 1A in the first embodiment, that is, by performing a multistatic operation, more virtual antennas are formed than in the positioning system 1A according to the first embodiment. If the number of virtual antennas formed by one radar 2 is N, and a multistatic operation is performed by M radars 2, N×M virtual antennas are formed in the positioning system 1A according to the first embodiment, while in the positioning system 1B according to the second embodiment, N×M 2 virtual antennas are formed.

[0059] For example, in the positioning system 1B shown in FIG. 10, transmission signals are emitted from the transmission antennas Tx of each radar 21, 22,..., 2 M and the antenna data Y1(1), Y1(2),..., Y1(M) formed by receiving the reflected waves from the target 11 by the receiving antenna Rx of the radar 21 are expressed as follows in the following equation (18).

Equation

[0060] Here, as shown in FIG. 10, the antenna data Y1(1) is data formed by radio waves emitted from the radar 21 and received by the radar 21, the antenna data Y1(2) is data formed by radio waves emitted from the radar 22 and received by the radar 21, and the antenna data Y1(M) is data formed by radio waves emitted from the radar 2 M and received by the radar 21. Also, the antenna data Y2(1) is data formed by radio waves emitted from the radar 21 and received by the radar 22, the antenna data Y2(2) is data formed by radio waves emitted from the radar 22 and received by the radar 22, and the antenna data Y2(M) is data formed by radio waves emitted from the radar 2 M and received by the radar 22. Also, the antenna data Y M (1) is data formed by radio waves emitted from the radar 21 and received by the radar 2 M , the antenna data Y M (2) is data formed by radio waves emitted from the radar 22 and received by the radar 2 M , and the antenna data Y M (M) is data formed by radio waves emitted from the radar 2 M and received by the radar 2 M .

[0061] Since the number of virtual antennas formed by one radar 21 is thus N×M, the number of virtual antennas formed by M radars is N×M 2 .

[0062] According to such a positioning system 1B according to the second embodiment, all that is required is synchronization of the transmission and reception timings between the respective radars 21 and 22. For this reason, as shown in FIG. 10, the transmission signal output by one of the plurality of radars 21, 22, …, 2 M can be received by the other radars 2. Therefore, the number of virtual antennas obtained by each of the radars 21, 22, …, 2 M increases as described above.

[0063] Therefore, in the convolution matrix C used in the AF method, more antenna data is stacked in the row direction of the matrix. For this reason, in the simultaneous equations represented by Equation (9) using the matrix product of the convolution matrix C and the filter coefficient vector H, the number of those equations increases further, and the filter coefficient vector H is represented more accurately. That is, in a general positioning system, the simultaneous equations represented by Equation (9) deteriorate in accuracy because the relationship between the estimated wave number K and the number of antennas N in Equation (7) is an ill-determined problem when K > (N - 1) / 2. However, also in the positioning system 1B according to the present embodiment, this condition is relaxed by stacking antenna data in the row direction of a plurality of rows, and the estimation accuracy is improved. Therefore, from the filter coefficient vector H represented more accurately, the inter-antenna phase difference w k is calculated more accurately, and the angle estimation of the target 11 can be performed with a higher angular resolution. However, similar to the first embodiment, it is a condition that the target position does not change during acquisition of each antenna data.

[0064] The graphs in FIGS. 11(a) and 11(b) show simulation results of virtual antennas formed by MIMO processing for one radar 2 (monostatic radar). The horizontal axis of each of these graphs represents the cross-range direction position, and the vertical axis represents the elevation direction position. In the graph of FIG. 11(a), the two transmitting antennas Tx of one radar 2 are represented by triangles, and the four receiving antennas Rx are represented by squares. In the graph of FIG. 11(b), the virtual antennas formed by these two transmitting antennas Tx and four receiving antennas Rx are represented by circles. As shown in the graphs of FIGS. 11(a) and 11(b), the number of virtual antennas formed by the two transmitting antennas Tx and four receiving antennas Rx in one radar 2 is 8 (= 2 × 4).

[0065] The graphs in FIGS. 11(c) and (d) show the simulation results of virtual antennas formed by MIMO processing for two radars 21 and 22 (bistatic radars). The horizontal and vertical axes of each of these graphs are the same as those of the graphs in FIGS. 11(a) and (b). In the graph of FIG. 11(c), the two transmitting antennas Tx respectively possessed by the two radars 21 and 22 are represented by triangles, and the four receiving antennas Rx are represented by squares. In the graph of FIG. 11(d), the virtual antennas formed by these two sets of two transmitting antennas Tx and four receiving antennas Rx are represented by circles. As shown in the graphs of FIGS. 11(c) and (d), the number of virtual antennas formed by two sets of two transmitting antennas Tx and four receiving antennas Rx in the two radars 21 and 22 is 32 (= 8 × 2 2 ) pieces. Due to the bistatic operation of the two radars 21 and 22, the 16 virtual antennas shown in frame A are increased.

[0066] The graph shown in FIG. 12(a) shows the comparison result between the RMSE (root mean square error) of angle estimation by the monostatic radar (one radar) shown in FIG. 11(a) and the RMSE of angle estimation by the bistatic radar (multiple radars) shown in FIG. 11(c) when the installation angle difference between two targets is changed. The horizontal axis of the graph represents the installation angle difference Δθ between two targets, target 11a and target 11b, shown in the plan view of FIG. 12(b). The vertical axis of the graph represents the RMSE. Also, the characteristic line 21 with each plot connected by a dotted line shows the result of simulating the RMSE in angle estimation by the monostatic radar, and the characteristic line 22 with each plot connected by a solid line shows the result of simulating the RMSE in angle estimation by the bistatic radar. Since the RMSE is the square root after the mean square of the difference between the true value and the measured value, the smaller the value, the more accurate it is.

[0067] As shown in the same graph, the characteristic line 22 is plotted at a position with a smaller RMSE than the characteristic line 21, indicating that the angle estimation by the bistatic radar is more accurate. Also, for example, in terms of angular resolution, when the point where the RMSE on the vertical axis matches half of the angular difference between two targets which is the value on the horizontal axis is used as the criterion, the angular resolution of the monostatic radar is about 5 deg (RMSE = 2.5 deg), while that of the bistatic radar is improved to about 3.5 deg (RMSE = 1.75 deg), which can be understood from the same graph.

[0068] Next, the positioning system according to the third embodiment of the present invention will be described.

[0069] The positioning system according to the third embodiment is different from the positioning system 1B according to the second embodiment in that the transmitting antenna Tx and the receiving antenna Rx are arranged such that the physical distances D between the transmitting antennas Tx and the receiving antennas Rx of each of the radars 21, 22,..., 2 M are different from each other. Other points are the same as those of the positioning system 1B according to the second embodiment.

[0070] The graphs shown in FIGS. 13(a) and (b) show the simulation results of MIMO processing for two radars 21 and 22 in the positioning system according to the third embodiment. The horizontal and vertical axes of each of these graphs are the same as those of the graphs in FIGS. 11(a) and (b). In the graph of FIG. 13(a), the two transmitting antennas Tx of each of the two radars 21 and 22 are represented by triangles, and the four receiving antennas Rx are represented by quadrangles. The physical distance D between the transmitting antenna Tx and the receiving antenna Rx of radar 21 is D1, and the physical distance D between the transmitting antenna Tx and the receiving antenna Rx of radar 22 is D2, and D1 and D2 are set to different distances (D1 ≠ D2).

[0071] In the graph of Fig. 13(b), the virtual antennas formed by these two pairs of two transmitting antennas Tx and four receiving antennas Rx are represented by circles. As shown in the graphs of Figs. 13(a) and 13(b), the number of virtual antennas formed by two radars 21 and 22 with the physical distance D1 and the physical distance D2 between the transmitting antenna Tx and the receiving antenna Rx set to different distances is 32 (= 8 × 2 2 ) pieces. Due to the bistatic operation of the two radars 21 and 22, the 16 virtual antennas shown in frame A are increased.

[0072] The graphs shown in Figs. 14(a) and 14(b) show the simulation results of MIMO processing for two radars 21 and 22 with the physical distance D1 and the physical distance D2 between the transmitting antenna Tx and the receiving antenna Rx set to equal distances (D1 = D2). The graphs shown in Figs. 14(c) and 14(d) show the simulation results of MIMO processing for two radars 21 and 22 with the physical distance D1 between the transmitting antenna Tx and the receiving antenna Rx in radar 21 set to a shorter distance (D1 < D2) than the physical distance D2 between the transmitting antenna Tx and the receiving antenna Rx in radar 22. The graphs shown in Figs. 14(e) and 14(f) show the simulation results of MIMO processing for two radars 21 and 22 with the physical distance D1 between the transmitting antenna Tx and the receiving antenna Rx in radar 21 set to a longer distance (D1 > D2) than the physical distance D2 between the transmitting antenna Tx and the receiving antenna Rx in radar 22.

[0073] The horizontal axis and the vertical axis of each of these graphs are the same as those of the graphs in Figs. 11(a) and 11(b). Also, in the same figure, parts identical or corresponding to those in Fig. 13 are denoted by the same reference numerals and their description is omitted.

[0074] In the case of two radars 21 and 22 where the physical distance D1 and the physical distance D2 are set to be equal (D1 = D2) and the simulation results are shown in FIGS. 14(a) and 14(b), the number of virtual antennas is 24. However, in the case of two radars 21 and 22 where the physical distance D1 is set to be shorter than the physical distance D2 (D1 < D2) and the simulation results are shown in FIGS. 14(c) and 14(d), and in the case of two radars 21 and 22 where the physical distance D1 is set to be longer than the physical distance D2 (D1 > D2) and the simulation results are shown in FIGS. 14(e) and 14(f), the number of virtual antennas is 32, which is an increase compared to the case of the two radars 21 and 22 where the physical distance D1 and the physical distance D2 are equal (D1 = D2).

[0075] The graph shown in FIG. 15 shows the result of simulating the number of virtual antennas obtained when the distance difference ΔD between the physical distance D1 and the physical distance D2 between the transmitting antenna Tx and the receiving antenna Rx is changed for two radars 21 and 22. The horizontal axis of the graph represents the distance difference ΔD between the physical distance D1 and the physical distance D2, and the vertical axis represents the number of virtual antennas.

[0076] From the graph, the number of virtual antennas is minimized when the distance difference ΔD = 0, and increases when the distance difference ΔD ≠ 0. That is, according to the positioning system according to the third embodiment in which the physical distance D1 and the physical distance D2 are set to different distances, the number of virtual antennas increases. However, since the radars 21 and 22 are separate modules, it is assumed that they are sufficiently separated compared to the physical distances D1 and D2. This assumption is reasonable considering the actual use of the radars 21 and 22.

[0077] According to the positioning system according to the above-described third embodiment, each radar 21, 22,..., 2 M The number of virtual antennas obtained thereby is further increased compared to the positioning system 1B according to the second embodiment. Therefore, the system of linear equations represented by equation (9) using the matrix product of the convolution matrix C and the filter coefficient vector H has an even greater number of equations, and the filter coefficient vector H is represented with even higher accuracy. Therefore, from the filter coefficient vector H represented with even higher accuracy, the phase difference w between antennask It is calculated with higher accuracy, and the angle estimation of target 11 can be performed with a higher angular resolution. However, similar to the first and second embodiments, it is a condition that the target position does not change during the acquisition of each antenna data.

[0078] FIG. 16 is a diagram for explaining the effect of the positioning system 1B according to the second and third embodiments.

[0079] FIG. 16(a) shows detection points 31a of vehicle 31 that can be detected by a single radar 2 (monostatic radar) having three transmitting antennas Tx and four receiving antennas Rx. FIG. 16(b) shows detection points 31a of vehicle 31 that can be detected by a plurality of radars 21, 22, 23 (multistatic radars) having one transmitting antenna Tx and four receiving antennas Rx.

[0080] FIG. 16(a) shows that in the single radar 2, only the reflected wave from the detection point 31a hit by the transmitted wave shown by the solid line can be received, and the reflected wave from the transmitted wave shown by the broken line cannot be received. FIG. 16(b) shows that the receivable reflected waves are not limited to the reflected waves from the detection points 31a hit by the transmitted waves shown by the solid lines sent from the plurality of radars 21, 22, 23. That is, the reflected wave by the transmitted wave shown by the broken line sent from radar 21 is received by other radars 22, 23, and the reflected wave by the transmitted wave shown by the dashed-dotted line sent from radar 23 is received by other radars 21, 22, indicating that detection points 31a over a wide range of the vehicle 31 can be recognized. That is, according to the positioning system 1B having a plurality of radars 21, 22, 23, by increasing the aperture length of the radar, detection points 31a over a wide range of the vehicle 31 can be recognized.

[0081] FIG. 17 is a diagram for explaining the effects achieved by the vehicle 31 including the positioning system 1A or 1B according to the first or second or third embodiment. In this example, the vehicle 31 includes the positioning system 1A or 1B on the door. Therefore, the vehicle 31 can recognize, for example, a plurality of poles 41 that are present and spread around the vehicle 31 at the time of its start and prompt the driver to pay attention. According to this configuration, the vehicle 31 can be provided with the positioning system 1A or 1B capable of estimating the angle of a target such as the pole 41 with high angular resolution.

[0082] In addition, in each of the above embodiments, the case where the transceiver is a radar has been described. However, the transceiver is not limited to a radar and may be a transceiver or the like, and in this case, the same operational effects as those of each of the above embodiments are achieved.

[0083] Also, in each of the above embodiments, the case where the signal processing unit is provided separately from the radar has been described. However, the signal processing unit may be provided in the radar, or a part of the signal processing unit may be provided in the radar. In this case, the same operational effects as those of each of the above embodiments are achieved.

Description of Reference Numerals

[0084] 1A, 1B... Positioning system 2, 21, 22,..., 2 M ... Radar (transceiver) 3... Signal processing unit 4... Transceiver 4a... Low-frequency synchronization signal input terminal 5... RF signal generation unit 6... Mixer 7... ADC (Analog-to-Digital Converter) 8... Low-frequency synchronization signal generation unit 9... Cable 11... Target Tx... Transmitting antenna Rx... Cross-reference to related applications of receiving antenna

[0085] This application claims priority based on Japanese Patent Application No. 2022-072710 filed with the Japan Patent Office on April 26, 2022, and all disclosures thereof are incorporated herein by reference in their entirety.

Claims

1. A plurality of transceivers, each comprising a plurality of transmission antennas for transmitting radio waves and a plurality of reception antennas for receiving reflected waves from a target; A signal processing unit that performs angle estimation of the target using the Annihilating Filter method using an annihilating filter; and the signal processing unit generates a convolution matrix by stacking and synthesizing a plurality of antenna data obtained by the plurality of reception antennas in the row direction of a matrix; obtains the filter coefficient vector from a system of simultaneous equations expressed using the product of the convolution matrix, with the filter coefficient vector of the transfer function of the annihilating filter being unknown, and the filter coefficient vector of the annihilating filter; calculates the phase difference between antennas from the obtained filter coefficient vector; and performs an operation to estimate the arrival angle of the reflected wave from the target based on the calculated phase difference between antennas a positioning system.

2. Each of the plurality of transceivers includes a mixer that mixes a transmission signal and a reception signal to generate an intermediate frequency signal, The positioning system according to claim 1, further comprising a synchronization signal generation unit that synchronizes signal processing in the frequency band of the intermediate frequency signal among the transceivers.

3. In the plurality of transceivers, the physical distance between the transmission antenna and the reception antenna of one transceiver is different from the physical distance in other transceivers. The positioning system according to claim 2.

4. The physical distance between the transmission antenna and the reception antenna of one transceiver is smaller than the physical distance in other transceivers. The positioning system according to claim 3.

5. The physical distance between the transmission antenna and the reception antenna of one transceiver is larger than the physical distance in other transceivers. The positioning system according to claim 3.

6. A vehicle comprising the positioning system according to any one of claims 1 to 5.

7. In a positioning method for performing angle estimation of a target using the Annihilating Filter method using an annihilating filter, a step of generating a convolution matrix by stacking and synthesizing a plurality of antenna data obtained by a plurality of transmission antennas for transmitting radio waves and a plurality of reception antennas for receiving reflected waves from the target, which are respectively provided in a plurality of transceivers, in the row direction of a matrix; A step of obtaining the filter coefficient vector from a system of simultaneous equations represented by a matrix product of the convolution matrix with the filter coefficient vector of the transfer function of the nulling filter, where the filter coefficient vector is unknown; A step of calculating the inter-antenna phase difference from the obtained filter coefficient vector; A step of performing an operation of estimating the arrival angle of the reflected wave from the target based on the calculated inter-antenna phase difference A positioning method comprising the above steps.

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