JP2010271337A - Radar device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately estimate the number of incoming waves, in a radar system for estimating the number of the incoming waves by MUSIC method, Esprit method or the like. <P>SOLUTION: The distances and relative speeds (or directions) of targets are obtained based on beat signals, and stored as history information. Target positions in the incoming wave estimation are predicted from the stored history information. Prediction is made about whether two or more targets are aligned, from the predicted target positions, and the number of incoming waves is estimated based on the prediction result. Thus, based on the history information of the targets obtained in the last cycle, prediction is made about whether targets, which have not travelled in parallel in the last cycle, travel in parallel with each other in this cycle, or whether targets, which have travelled in parallel with each other in the last cycle, stop travelling in parallel in this cycle, and the number of incoming waves is revised. The number of incoming waves is thereby estimated more accurately. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a radar apparatus that obtains a positional relationship between a target object and itself by transmitting and receiving a frequency-modulated radar wave, and is applied to, for example, a radar apparatus used for collision prevention of a moving body such as a vehicle. It is preferable.

  Conventionally, an FMCW radar device is known (see, for example, Patent Document 1). This radar apparatus detects the relationship between the preceding vehicle and the host vehicle, for example, by extracting information on the relative distance and relative speed with the target object by transmitting and receiving a frequency-modulated radar wave. . In such a radar apparatus, when a frequency-modulated radar wave is transmitted / received, it is necessary to determine how much a target object such as another vehicle exists in front of the host vehicle and in which direction the target object exists. is there. The beam former method, the MUSIC method, the Esprit method, etc. are generally known as means for obtaining the orientation. Among them, when using the MUSIC (Multiple Signal Classification) method or the Esprit method, there is a feature that a high azimuth resolution can be obtained, but it is necessary to accurately estimate the number of incoming waves in the process of calculating the direction of the incoming wave.

  There are AIC (Akaike Information Criteria) and MDL (Minimum Description Length) as methods for estimating the number of incoming waves. In these methods, the number of incoming waves is estimated by collecting data a plurality of times and evaluating the dispersion.

  On the other hand, there is a method of setting a certain threshold value and distinguishing whether the eigenvalue is equivalent to noise power or signal power, and this method is called a threshold method. For example, Patent Document 2 discloses a method for estimating the number of incoming waves by the threshold method in the case of the MUSIC method.

  The estimation of the number of incoming waves by the threshold method in the case of the MUSIC method will be described with reference to FIG.

  FIG. 13 is a diagram illustrating a state where an incoming wave is input to an adaptive antenna in which a plurality of antennas are arranged in an array at equal intervals.

  As shown in this figure, it is assumed that when K antennas arranged at equal intervals are mounted on a vehicle, a plurality of radio waves are input to each antenna as incoming waves from a distance from the vehicle. In this case, since the distance between each antenna and the target object that is the transmission source of the incoming wave is sufficiently longer than the distance between the antennas, it can be assumed that the incoming wave is input to each antenna at the same angle. In addition, the phase of the incoming wave input to each antenna varies depending on the direction of the incoming wave.

  For this reason, if the received data (vector) of the incoming wave input to each antenna is represented by xi (t), (i = 1 to k), the output is obtained when each incoming wave is converted into the output voltage Pout. The weight Wmin when the voltage Pout is minimized is expressed by the following equation.

ただし、Ｒｘｘは到来波の受信データｘｉ（ｔ）の自己相関行列を示している。また、Ｗはウェイト、Ｗ^HはＷの共役転換行列を示しており、Ｗ^HＷ＝１である。

Here, Rxx represents an autocorrelation matrix of incoming wave reception data xi (t). W is a weight, W ^H is a conjugate conversion matrix of W, and W ^H W = 1.

  Here, the following equation can be defined using the eigenvalue λ by Lagrange's undetermined coefficient method.

(Equation 2)
RxxW = λW
Then, the following equation is derived by multiplying both sides of this equation by ^WH .

(Equation 3)
W ^H RxxW = λW ^H W = λ
At this time, λ corresponds to twice the output voltage Pout when the weight W is multiplied. That is, when a directional null point (zero point) is directed in the direction of the incoming wave and W can be set so that the output voltage Pout in the direction of the incoming wave becomes the minimum value, the signals from all the incoming waves are canceled. Can be equal to noise. Conversely, when there is an incoming wave to which the null point is not directed, the signal from the incoming wave to which the null point is not directed cannot be canceled, and λ has a value. Therefore, when the eigenvalue λ of the autocorrelation matrix Rxx is expressed, the eigenvalues λ1 to λK obtained from the reception data obtained by the K antennas have the following relationship.

なお、σ²は、熱雑音電力に相当する。

Note that σ ² corresponds to thermal noise power.

For this reason, the eigenvalue of the autocorrelation matrix Rxx can be obtained, and the number of incoming waves L can be estimated from the number of eigenvalues greater than the thermal noise power σ ² . That is, it is possible to estimate the number of incoming waves L by setting a threshold between λL and λL + 1 shown in Equation 4 and determining whether the eigenvalue λ exceeds the threshold λTH. Further, the region exceeding the threshold λTH is a noise space in which signals from all incoming waves can be canceled, and the region lower than λTH is a signal space in which signals from at least one incoming wave cannot be canceled. Become. Therefore, the noise space in which the signals from all the incoming waves can be canceled is the one in which the signals corresponding to the number of incoming waves can be canceled, and based on this, the direction of the incoming wave can be calculated. .

Japanese Patent Laid-Open No. 11-030663 JP 2000-121716 A

Nobuyoshi Kikuma, Adaptive Antenna Technology, Ohm, P.A. 138-P. 139 (MUSIC), P.I. 145-P. 150 (Esprit)

  In any of these methods, the more the number of data collections (snapshots) and the larger the received signal SN ratio (signal-noise ratio), the more accurately the number of incoming waves can be estimated. it can. That is, when the number of data is small, accurate estimation of the number of incoming waves cannot be performed.

  However, when the MUSIC method or Esprit method is applied to an on-vehicle radar device, if the relative relationship between the target and the radar is fast and the usable computing power is low, a large amount of data in the same situation is collected. It is impossible to do. Furthermore, when there are a plurality of reflecting objects around, it is difficult to secure a stable SN ratio due to the influence of multipath. Under these circumstances, it is difficult to accurately estimate the number of incoming waves, and there is a problem in that it may cause a false detection or no detection of the target.

  In view of the above points, the present invention enables estimation of the number of incoming waves with high accuracy in a radar apparatus that estimates the direction of the incoming wave after estimating the incoming wave using eigenvalue decomposition such as the MUSIC method and the Esprit method. The purpose is to propose a new method.

  In order to achieve the above object, the invention according to claim 1 has history information storage means for obtaining the distance and relative speed (or direction) of the target based on the beat signal and storing them as history information, The arrival wave number estimation means has target position prediction means (400) for predicting the position of the target in the current arrival wave estimation from the history information stored in the history information storage means. It is characterized by predicting whether or not a plurality of targets are arranged from the position of the target to be estimated, and estimating the number of incoming waves based on the prediction result.

  Thus, based on the target history information obtained during the previous cycle, whether targets that were not running in parallel during the previous cycle run in parallel during the current cycle, or In addition, it is predicted whether or not the targets that have been running in parallel in the previous cycle will not run in parallel in the current cycle, and the number of incoming waves is corrected based on the prediction. As a result, the number of incoming waves can be estimated more accurately.

  For example, as described in claim 2, the arrival wave number estimation means obtains the number of targets predicted to be arranged in the current arrival wave estimation from the target position predicted by the target position prediction means, and this number And the number of targets lined up at the time of the previous arrival wave estimation are the number of arrival waves estimated at the previous arrival wave estimation and the arrival wave estimated at the current arrival wave estimation. If the number of targets does not match the number of incoming signals, the number of incoming waves estimated during the previous incoming wave estimation is The number of incoming waves is estimated by adding or subtracting the difference from the number of targets lined up at the time of incoming wave estimation.

  According to a third aspect of the present invention, it is predicted whether or not a plurality of targets are arranged from the target positions predicted by the target position predicting unit, and the threshold (λ that is set by the threshold setting unit based on the prediction result) Even if the value of) is adjusted, the same effect as in the first or second aspect can be obtained.

  In addition, the code | symbol in the bracket | parenthesis of each said means shows the correspondence with the specific means as described in embodiment mentioned later.

It is a figure which shows the block configuration of the radar apparatus in 1st Embodiment of this invention. It is a flowchart of the process of MUSIC which the signal processing part of the radar apparatus shown in FIG. 1 performs. It is a flowchart of the arrival wave number estimation process which the signal processing part of the radar apparatus shown in FIG. 1 performs. (A) is the figure which showed the correlation of beat frequency [bin] and eigenvalue (lambda), (b) is the figure which showed the relationship between the noise according to a beat frequency, and a beat signal. It is the schematic diagram which showed the relationship between the output azimuth | direction area | region of the electromagnetic wave of the millimeter wave band output from a transmission antenna, and the maximum number which a vehicle can run in parallel in the area. 10 is a flowchart of arrival wave number estimation processing executed by a signal processing unit of a radar apparatus according to a second embodiment. It is the schematic diagram which showed the positional relationship of the own vehicle and other vehicle of the last cycle and this cycle. 10 is a flowchart of arrival wave number estimation processing executed by a signal processing unit of a radar apparatus according to a third embodiment. 10 is a flowchart of arrival wave number estimation processing executed by a signal processing unit of a radar apparatus according to a fourth embodiment. It is a flowchart of the arrival tooth number estimation process in 5th Embodiment. It is a flowchart of the process which calculates | requires the determination of the correct number of incoming waves, the direction of the incoming waves, and reception power. It is a flowchart of the process which calculates | requires the determination of the correct number of incoming waves, the direction of the incoming waves, and reception power in 6th Embodiment. It is the figure which showed a mode when an incoming wave was input with respect to the adaptive antenna with which the several antenna was arranged in the array form at equal intervals.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following embodiments, the same or equivalent parts are denoted by the same reference numerals in the drawings.

(First embodiment)
A block configuration of an in-vehicle radar device to which an embodiment of the present invention is applied is shown in FIG. Hereinafter, the configuration of the radar apparatus according to the present embodiment will be described with reference to FIG.

  The radar device emits millimeter wave radio waves in the traveling direction of the vehicle, for example, forward, and receives the radio waves reflected by the target object such as the preceding vehicle as incoming waves. As well as the distance to the target object and the relative speed with respect to the host vehicle.

  As shown in FIG. 1, the radar apparatus includes a modulation signal generation unit 1, a voltage controlled oscillator 2, a distributor 3, a transmission antenna 4, a reception unit 5, a mixer 6, an A / D converter 7, and a signal processing unit. 8 is provided.

  For example, the modulation signal generation unit 1 generates a triangular wave-shaped modulation signal having a predetermined period for performing modulation such that the frequency linearly increases or decreases with respect to time. The modulation signal generated by the modulation signal generator 1 is output to the voltage control transmitter 2.

  The voltage controlled oscillator 2 generates a high frequency signal in the millimeter wave band as a transmission signal. The voltage-controlled oscillator 2 controls the frequency of the high-frequency signal according to the modulation signal based on the modulation signal output from the modulation signal generator 1 and outputs it to the distributor 3.

  The distributor 3 distributes the power of the transmission signal output from the voltage controlled oscillator 2 and generates a local signal. The local signal from the distributor 3 is input to the mixer 6.

  The transmission antenna 4 outputs a millimeter wave band radio wave indicated by the transmission signal output from the voltage controlled oscillator 2 via the distributor 3 in the traveling direction of the vehicle, for example, forward.

  The receiving unit 5 constitutes an adaptive antenna in which k antennas 5a are arranged in an array at equal intervals, and xi (t) that is received data (received signals) of incoming waves input to the plurality of antennas 5a. , (I = 1 to K), and a switch 5c for combining the received data xi (t) obtained by the receiving unit 5b and transmitting them to the high-frequency mixer 6. .

  The mixer 6 mixes the combination of the received data xi (t) transmitted from the receiving unit 5 and the local signal transmitted from the distributor 3, and generates a beat signal that is a frequency component of the difference between these signals. is there. The frequency of the beat signal generated at this time is called the beat frequency. The beat frequency when the frequency of the transmission signal increases and the beat frequency when the frequency of the transmission signal decreases and the beat frequency when the frequency of the transmission signal decreases and downstream modulation. This is called the beat frequency of the hour, and is used to calculate the distance and relative speed of the target object by the FMCW method.

  The A / D converter 7 is for converting the beat signal shown as an analog value output from the mixer 6 into a digital value.

  The signal processing unit 8 is configured by a known microcomputer including a CPU, a ROM, a RAM, an I / O, and the like, and executes a process according to a program stored in the ROM or the like. Specifically, the signal processing unit 8 estimates (calculates) the number and directions of incoming waves based on the MUSIC process based on the beat signal converted into a digital value by the A / D converter 7 and uses FMCW. The distance and relative speed are calculated. Note that the information on the number and direction of incoming waves, the distance and relative velocity of the target object calculated by the signal processing unit 8 is sequentially stored in, for example, a RAM, and remains as history information at least until the next calculation cycle. ing. In the signal processing unit 8, the part that stores the history information corresponds to the history information calculation means.

  Next, processing executed by the radar apparatus configured as described above will be described with reference to flowcharts of processing shown in FIGS.

  FIG. 2 shows the estimation of the number and direction of incoming waves based on the MUSIC process, and FIG. 3 shows the details of the incoming wave number estimation process executed during the MUSIC process. The processing shown in each of these figures is executed by the signal processing unit 8 in the radar apparatus. For example, when a switch (not shown) for executing auto-cruise control is pressed during the use period of the radar apparatus. To be executed.

  First, in step 100, a process for obtaining received data xi (t) is executed. This process is performed by extracting the received data xi (t) from the beat signal.

  In step 110, the autocorrelation matrix Rxx is calculated based on the received data xi (t). In step 120, the eigenvalue λ (λ1 to λK) and the eigenvector when the autocorrelation matrix Rxx calculated in step 110 is obtained. En and Es are calculated. Here, the eigenvector En here corresponds to the weight W multiplied in calculating the eigenvalue λ of the noise space described above, and the eigenvector Es is multiplied in calculating the eigenvalue λ of the signal space. This corresponds to the weight W. Since the calculation method of the autocorrelation matrix Rxx and the calculation method of the eigenvalue λ and the eigenvectors En and Es are the same as those in the related art, the description thereof is omitted here. As described above, the part for calculating the autocorrelation matrix Rxx in the signal processing unit 8 corresponds to the autocorrelation matrix calculation means, and the part for calculating the eigenvalue corresponds to the eigenvalue calculation means.

  In step 130, an incoming wave number estimation process is executed. In this incoming wave number estimation process, each process shown in the flowchart of FIG. 3 is executed. The portion of the signal processing unit 8 that executes this arrival wave number estimation process corresponds to the arrival wave number estimation means.

  When the arrival wave number estimation process is executed, first, in step 200, the thresholds λTH1 to λTH256 for each beat frequency are read. The thresholds λTH1 to λTH256 for each beat frequency here are obtained from the correlation between the beat frequency [bin] and the eigenvalue λ shown in FIG. 4A, and are obtained, for example, from the results of experiments performed in advance. . For example, as noise corresponding to the beat frequency, unnecessary signals such as FM-AM conversion noise, 1 / f noise, thermal noise, and reflection from the road surface are generated as shown in FIG. 4B. Since these are correlated with the beat frequency, the thresholds λTH1 to λTH256 shown in FIG. 4A are obtained by drawing a line between the sum of the unnecessary signals and the beat signal. The thresholds λTH1 to λTH256 are stored as maps in the ROM of the signal processing unit 8, for example. Accordingly, in step 200, the thresholds λTH1 to λTH256 stored as this map are read.

  In the following step 210, the threshold λTH corresponding to the beat frequency of the beat signal input to the signal processing unit 8 is read from the correlation between the beat frequency stored in the map and the thresholds λTH1 to λTH256, and the beat frequency at that time is read. The corresponding threshold λTH is set. The portion for setting the threshold as described above corresponds to the threshold setting means.

  Then, in step 220, the eigenvalues λ (λ1 to λK) obtained in step 120 described above are input, and in step 230, it is determined whether or not each of the eigenvalues λ (λ1 to λK) is larger than the threshold λTH. . As a result, as shown in step 240 and step 250, each eigenvalue λ (λ1 to λK) is divided into eigenvalues λ1 to λL in the signal space and eigenvalues λL + 1 to λK in the noise space. In the flowchart shown in FIG. 3, the eigenvalue λx obtained from the received data of the arbitrary (xth) receiving antenna 5a is shown as whether or not the eigenvalue λx is larger than the threshold λth. λ (λ1 to λK) is representatively represented.

  In step 260, the number of incoming waves L is estimated from the number of eigenvalues λ1 to λL in the signal space. This makes it possible to accurately estimate the number of incoming waves L taking into account unnecessary signals such as noise.

  When the arrival wave number is estimated in this way, a MUSIC spectrum is calculated in step 140 based on the obtained arrival wave number. The method for calculating the MUSIC spectrum is the same as in the prior art.

  Subsequently, in step 150, the direction of the incoming wave is calculated based on the peak wave of the original incoming wave obtained in step 140. That is, by looking at the distribution of the peak wave of the arriving wave, it is possible to obtain the direction in which the beam of the receiving antenna corresponding to the peak wave of the arriving wave is directed. This direction is calculated as the direction in which the target object exists.

  In step 160, reception power is calculated. The received power information is used as information for a process of searching for a pair of beat frequencies in both up / down modulation in FMCW (known as a pairing process), and a distance from the target object and a relative speed are calculated.

  As described above, in the present embodiment, in the arrival wave number estimation process, the threshold λTH is set in consideration of unnecessary signals such as noise, and the eigenvalues λ1 to λK of the incoming wave are determined based on the threshold λTH in the signal space. The eigenvalues λ1 to λL of the noise and the eigenvalues λL + 1 to λK of the noise space are discriminated.

  As a result, the number of incoming waves L can be accurately estimated from the number of eigenvalues λ1 to λL in the signal space in consideration of noise. Therefore, it is possible to execute the auto cruise control based on the accurately estimated arrival wave number L, and it is possible to execute more appropriate auto cruise control.

(Second Embodiment)
A second embodiment of the present invention will be described. The radar apparatus of this embodiment is obtained by changing the arrival wave number estimation process executed by the signal processing unit 8 with respect to the first embodiment, and the others are the same as those of the first embodiment, and therefore only different parts will be described. To do.

  As described above, the present embodiment limits the maximum value of the number of incoming waves estimated according to the output direction area of the radio wave in the millimeter wave band output from the transmitting antenna 4 in addition to the incoming wave estimation considering noise. To do. This will be described with reference to FIG.

  FIG. 5 is a schematic diagram showing a relationship between an output azimuth area of millimeter wave radio waves output from the transmission antenna 4 and a maximum number of vehicles that can run in parallel in the area.

  As shown in this figure, since the width of the output azimuth area is uniquely determined from the distance from the own vehicle, the number of vehicles (targets) that can run in parallel in the output azimuth area is inevitably determined. For example, when the angle of the output azimuth area is about 10 degrees on the left and right with respect to the front of the vehicle, it is assumed that the lateral width of the vehicle is about 1.7 m and the pitch between parallel running vehicles is about 3.1 m. Then, if it is about 17-18m away from the own vehicle, only a plurality of vehicles can run in parallel. Therefore, when the maximum value Lmax of the number of incoming waves is determined for each output azimuth area and the number of incoming waves exceeding the maximum value is estimated, it cannot be said that it is appropriate. For this reason, in this embodiment, the maximum value Lmax of the number of incoming waves is limited for each output azimuth area.

  FIG. 6 shows a flowchart of the arrival wave number estimation process executed by the signal processing unit 8 in the radar apparatus of this embodiment.

  First, in steps 200 to 250, processing similar to that in the first embodiment is executed. In step 300, the maximum value Lmax (Lmax1, Lmax2,...) Of the number of incoming waves for each output azimuth area is read out. The maximum value Lmax is determined according to the distance from the host vehicle based on the above-described consideration, and is stored in the signal processing unit 8 as a map. For this reason, the map stored in the signal processing unit 8 is read.

  In step 310, the maximum value Lmax is set based on the read map. Specifically, in the radar apparatus, distance and relative speed are calculated by the FMCW method based on the received power as shown in FIG. For this reason, the calculation result here is used as area information (distance information) of the target object to be a target, and a maximum value Lmax corresponding to the area information is set. The part for setting the maximum value of the number of incoming waves as described above corresponds to the incoming wave maximum value setting means.

  In step 320, it is determined whether or not the number of incoming waves L obtained from the eigenvalues λ1 to λL of the signal space sorted as in step 240 is equal to or less than the maximum value Lmax. If an affirmative determination is made here, the incoming wave number L is equal to or less than the number of vehicles that can physically run in parallel, and it is assumed that there is no contradiction. Output as wave number L.

  On the other hand, if a negative determination is made here, the number of incoming waves L is equal to or greater than the number of vehicles that can physically run in parallel, and the process proceeds to step 330 as inconsistent. In this step, Lmax is set as the incoming wave number L and is output in step 260.

  As described above, in the present embodiment, the number of vehicles that can physically run in the output azimuth area is limited as the maximum value Lmax of the number of incoming waves L, and the number of incoming waves exceeding that is estimated. In such a case, the maximum value Lmax is set as the number of incoming waves L as contradictory. This makes it possible to estimate the arrival wave number L more accurately.

(Third embodiment)
A third embodiment of the present invention will be described. The radar apparatus of this embodiment is obtained by changing the arrival wave number estimation process executed by the signal processing unit 8 with respect to the first embodiment, and the others are the same as those of the first embodiment, and therefore only different parts will be described. To do.

  In the present embodiment, in addition to the second embodiment, whether or not to run in parallel in the next cycle is predicted from the history information of the radar apparatus, and the number of incoming waves is estimated according to the prediction result. This will be described with reference to FIG.

  FIG. 7 shows that when there are a plurality of preceding vehicles, in the previous cycle, the other vehicle located on the side closer to the own vehicle was separated from the other vehicle located on the far side. This shows a case where the other vehicle located on the near side runs in parallel with the other vehicle located on the far side.

  In the previous cycle, the beat frequency determined by the distance and relative speed between the host vehicle and each other vehicle is different, so the incoming waves from each other vehicle are detected as coming from different areas, The number of incoming waves will be estimated. That is, the arrival wave number is estimated in a form where the arrival wave number is 1 in the area where the other vehicle nearer to the own vehicle is present and the arrival wave number is 1 in the area where the other vehicle far from the own vehicle exists.

  On the other hand, at the time of this cycle, the beat frequencies determined by the distance and relative speed between the host vehicle and the two other vehicles are the same, and the incoming waves from the two other vehicles arrive in the same area. The wave number will be estimated.

  Therefore, if it is predicted from the distance and relative speed of the preceding vehicle obtained during the previous cycle that the preceding vehicle will run in parallel with other preceding vehicles during the current cycle, this is calculated as the number of incoming waves. Used for estimation.

  FIG. 8 shows a flowchart of the arrival wave number estimation process executed by the signal processing unit 8 in the radar apparatus of this embodiment.

  First, in steps 200 to 250 and steps 300 to 330, processing similar to that in the second embodiment is executed. In step 400, the target position prediction in the current cycle is performed from the history information of the target (preceding vehicle) obtained at the previous cycle by the radar apparatus. As a result, when other vehicles that were not running in parallel in the previous cycle are predicted to run in parallel in the current cycle, the value obtained by adding the previous number of incoming waves is set as the predicted number of incoming waves. Will be. Note that such a target position prediction portion corresponds to the target position prediction means.

  In step 410, it is determined whether a value obtained by adding one to the previous arrival wave number is set, and the arrival wave number L set in step 320 or step 330 is 1 with respect to the previous arrival wave number. It is determined whether or not a value obtained by adding the two is not reached. As a result, when a value obtained by adding one to the previous number of incoming waves is set and the incoming wave number L is not a value obtained by adding one to the previous number of incoming waves, step 320 is performed. Alternatively, assuming that the incoming wave number L set in step 330 is incorrect, the routine proceeds to step 420 where the incoming wave number L is changed to L + 1. In addition, when the value obtained by adding one to the previous arrival wave number is not set, or even when the value obtained by adding one to the previous arrival wave number is set, the arrival wave number L is the previous arrival wave number. If the value is a value obtained by adding one to, the number of incoming waves L set in step 320 or step 330 is assumed to be correct, and the process proceeds to step 260 as it is. Then, the incoming wave number L is output at step 260.

  As described above, in this embodiment, based on the target history information obtained at the previous cycle, whether the targets that were not running at the previous cycle run in parallel at the current cycle. And the number of incoming waves L is corrected based on the prediction. This makes it possible to estimate the arrival wave number L more accurately.

(Fourth embodiment)
A fourth embodiment of the present invention will be described. As in the third embodiment, the radar apparatus of this embodiment is based on the target history information obtained at the previous cycle, and targets that were not running in parallel at the previous cycle are Whether to run in parallel is predicted, and the number of incoming waves L is obtained based on the prediction. Here, the number of incoming waves is estimated based on the prediction by lowering the threshold λTH.

  FIG. 9 shows a flowchart of the arrival wave number estimation process executed by the signal processing unit 8 in the radar apparatus of the present embodiment.

  First, in steps 200 to 210, processing similar to that in the first embodiment is executed. In step 500, the target position in the current cycle is predicted from the history information of the target (preceding vehicle) obtained at the previous cycle by the radar apparatus. As a result, when other vehicles that were not running in parallel in the previous cycle are predicted to run in parallel in the current cycle, the value obtained by adding the previous number of incoming waves is set as the predicted number of incoming waves. Will be.

  In step 510, it is determined whether or not a value obtained by adding one to the previous number of incoming waves is set. If an affirmative determination is made in this step, the process proceeds to step 520, the threshold λTH is decreased by α, and then the process proceeds to step 230. If a negative determination is made, the process proceeds to step 230 as it is.

  Here, α is set to such a value that the number of eigenvalues λ1 to λL in the signal space is assumed to increase by one, and is obtained experimentally, for example.

  Thereafter, in step 230, it is determined whether each eigenvalue λ (λ1 to λK) is larger than the threshold λTH. Thereafter, the same processing as in the second embodiment is executed.

  As described above, according to the present embodiment, based on the target history information obtained at the previous cycle, whether the targets that were not running at the previous cycle run in parallel at the current cycle. The number of incoming waves L is corrected by correcting the threshold λTH based on the prediction. This makes it possible to estimate the arrival wave number L more accurately.

(Fifth embodiment)
A fifth embodiment of the present invention will be described. The radar apparatus of this embodiment is almost the same as that of the third embodiment, but the number of incoming waves is fixed to an arbitrary initial value (L = L0, for example, L0 = 2, 3), and based on the initial value. The temporary arrival wave number L is obtained, and the actual arrival wave number L is finally obtained from the temporary arrival wave number L based on the received power.

  FIG. 10 shows a flowchart of the arrival wave number estimation process executed by the signal processing unit 8 in the radar apparatus of this embodiment. In the case of the present embodiment, a temporary incoming wave number L is first obtained by this incoming wave number estimation process. In addition, the part which performs this process among the signal processing parts 8 is equivalent to temporary arrival wave number estimation means.

  In step 220, the eigenvalue λ (λ1 to λK) is input as in the third embodiment. In step 600, the initial value of the incoming wave number L is set, and the initial value of the incoming wave number L is fixed as the incoming wave number L = L0. Based on this, in step 610, the eigenvalue λ (λ1 to λL) of the signal space and the eigenvalue λ (λL + 1 to λK) of the noise space are obtained in the same manner as in steps 240 and 250 shown in FIG.

  Thereafter, the processing of steps 300 to 330 and steps 400 to 420 and step 260 shown in the third embodiment is executed, so that the incoming wave number L is estimated. And the value calculated | required in this way is made into the temporary number L of incoming waves. Thereby, the arrival wave number estimation process is completed.

  When this arrival wave number estimation process is completed, a MUSIC spectrum is calculated using a conventional method based on the calculated temporary arrival wave number, as shown in step 140 of FIG. In addition, the part which performs this process among the signal processing parts 8 is equivalent to a MISIC spectrum calculation means.

  FIG. 11 is a flowchart of processing for determining the correct number of incoming waves L and obtaining the direction of the incoming waves and the received power in the radar apparatus of this embodiment. This process is executed as equivalent to each of the processes in step 150 and step 160 in FIG. Of the signal processing unit 8, the part that executes this processing corresponds to the azimuth detecting means and the received power detecting means.

  First, in step 700, peak wave directions (hereinafter referred to as peak search directions) D1 to DL and received powers P1 to PL confirmed from the MUSIC spectrum obtained in step 140 are detected. Here, since the number of provisional incoming waves is set to L in step 260 described above, the number of peak waves is also set to the same L. The method for calculating the peak search directions D1 to DL and the received powers P1 to PL is the same as in steps 150 and 160 described above.

  Next, in step 710, the received power thresholds PTH1 to PTH256 for each beat frequency are read. The thresholds PTH1 to PTH256 of the reception power for each beat frequency here are obtained from the correlation between the beat frequency [bin] and the reception power, and are obtained from, for example, a result of an experiment performed in advance.

  In the following step 720, the received power threshold PTH corresponding to the beat frequency of the beat signal input to the signal processing unit 8 is read from the correlation between the beat frequency stored in the map and the received power thresholds PTH1 to PTH256, It is set as a threshold PTH of received power corresponding to the beat frequency at that time. The portion for setting the threshold as described above corresponds to the threshold setting means.

  In step 730, it is determined whether or not the received power P1 to PL obtained in step 700 exceeds the received power threshold PTH corresponding to the beat frequency set in step 720. Of these, only the wave exceeding the threshold PTH is regarded as an actually existing incoming wave. Then, using the information on the actual direction of the incoming wave and the received power, the direction in which the target object exists, the distance from the target object, and the relative velocity are obtained.

  As described above, in the present embodiment, the incoming wave number L is fixed to an arbitrary initial value, and the temporary incoming wave number L is obtained based on the initial value, and then reception of each direction of the temporary incoming wave is received. It is determined whether or not the power exceeds the threshold PTH, and those that do not exceed the threshold are removed from the incoming wave, thereby obtaining the actual incoming wave number L. As a result, the actual number of incoming waves L can be obtained accurately, and the same effect as in the first embodiment can be obtained.

(Sixth embodiment)
A sixth embodiment of the present invention will be described. The radar apparatus according to the present embodiment executes the process shown in FIG. 12 instead of the process shown in FIG. 11 with respect to the fifth embodiment. Since other aspects are the same as those of the fifth embodiment, description thereof is omitted.

  FIG. 12 is a flowchart of processing for determining the correct number of incoming waves L and obtaining the direction of the incoming waves and the received power in the radar apparatus of this embodiment. This process is executed as equivalent to each of the processes in step 150 and step 160 in FIG.

  First, in step 700, peak search directions D1 to DL are detected from the MUSIC spectrum obtained in step 140.

  Next, in step 740, received powers P1 to PL at the peak search directions D1 to DL are calculated. Specifically, the received powers P1 to PL are obtained by the following equation and extracted from the diagonal components of S (see Nobuyoshi Kikuma, Adaptive Antenna Technology, Ohmsha, P.137-P.141).

(Equation 5)
S = (A ^H A) ⁻¹ A ^H (Rxx−σ ² I) A (A ^H A) ⁻¹
Here, S is a signal (wave source) correlation matrix, A is a direction matrix, Rxx is an autocorrelation matrix of received data xi (t) of incoming waves, and I is a unit matrix.

  In steps 710 and 720, the same processing as in the fifth embodiment is performed. In step 730, it is determined whether or not the received power P1 to PL obtained in step 750 exceeds the received power threshold PTH corresponding to the beat frequency set in step 720. Of these, only the wave exceeding the threshold PTH is regarded as an actually existing incoming wave. Using the information on the actual direction of the incoming wave and the received power, the direction in which the target object exists, the distance from the target object, and the relative velocity are obtained.

  As described above, in this embodiment as well, as in the fifth embodiment, the incoming wave number L is fixed to an arbitrary initial value, and the temporary incoming wave number L is obtained based on this initial value. It is determined whether or not the received power in each direction of the incoming wave exceeds the threshold PTH, and those not exceeding are removed from the incoming wave to obtain the actual incoming wave number L. As a result, the actual number of incoming waves L can be obtained accurately, and the same effect as in the first embodiment can be obtained.

(Other embodiments)
In the first to fourth embodiments, the on-vehicle radar device has been described as an example, but the present invention can also be applied to other radar devices. However, it is particularly preferable to apply the present invention to an on-vehicle radar device that is mounted on a vehicle that moves at high speed and that cannot be expected to have high device performance.

  In the third and fourth embodiments, based on the target history information obtained during the previous cycle, it is predicted whether the targets that were not running in parallel during the previous cycle will run in parallel during the current cycle. The incoming wave number L is corrected based on the prediction. On the other hand, based on the target history information obtained during the previous cycle, it is predicted that the targets that were running in parallel during the previous cycle will not run in parallel during the current cycle. It is also possible to correct the number of incoming waves L.

  In this case, in the third embodiment, the number of incoming waves L is corrected to L−1, and in the fourth embodiment, the number of eigenvalues λ is reduced by increasing the threshold λTH.

  Of course, only the case where the number of parallel running targets increases or decreases is described here, but in the case of a plurality of targets, the number increases or decreases by that number.

  That is, the number of targets predicted to be arranged in the arrival wave estimation in the current cycle is obtained, and the difference between this number and the number of targets arranged in the previous cycle is obtained. And if it does not match the difference between the number of incoming waves estimated during the previous cycle and the number of incoming waves estimated during the current cycle, it was estimated during the previous cycle. The difference between the number of targets expected to be arranged in the current cycle and the number of targets arranged in the previous cycle is added to or subtracted from the number of incoming waves. This makes it possible to estimate the number of incoming waves according to the number of parallel targets.

  Further, in each of the above embodiments, the MUSIC method has been described as an example. However, a radar device that estimates the direction of the incoming wave after estimating the number of incoming waves using eigenvalue decomposition, such as the Esprit method and the unitary MUSIC method The present invention can also be applied to a radar apparatus using the unitary Esprit method or the like.

  Further, in the above embodiment, the case where the distance and relative speed are obtained from the beat signal by FMCW is exemplified, but the present invention is not limited to this, and it is also possible to adopt a two-frequency CW, a pulse method, and a spread spectrum method. . When the FMCW method is applied, the thresholds λTH1 to λTH256 for each beat frequency are set. When the two-frequency method or the multi-frequency CW method is applied, for each phase of the beat signal. In addition, when the pulse method or the spread spectrum method is applied, the threshold is set for each delay time of the beat signal, that is, for each distance to the target.

  In the above embodiment, the case where 256 thresholds λTH and PTH are set, such as the thresholds λTH1 to λTH256 and PTH1 to PTH256 for each beat frequency, has been described, but the number of thresholds λTH and PTH is an arbitrary number n. The thresholds λTH1 to λTHn and PTH1 to PTHn for each beat frequency can be set.

  The steps shown in each figure correspond to means for executing various processes.

  DESCRIPTION OF SYMBOLS 1 ... Modulation signal production | generation part, 2 ... Voltage control oscillator, 3 ... Distributor, 4 ... Transmission antenna, 5 ... Reception part, 6 ... Mixer, 7 ... A / D converter, 8 ... Signal processing part.

Claims (3)

A transmission signal is transmitted through the transmission antenna (4), and a plurality of incoming waves arriving from a plurality of directions are received via a plurality of antennas (5a) arranged at different positions, and a reception signal for each antenna is received. From the radar apparatus for estimating the direction of the incoming wave from the target reflecting the transmission signal,
Beat signal means (6) for generating a beat signal that is a frequency component of a difference between the transmission signal and the reception signal;
Autocorrelation matrix calculating means (110) for calculating an autocorrelation matrix (Rxx) based on the beat signal;
Eigenvalue calculating means (120) for calculating the eigenvalue (λ) from the autocorrelation matrix calculated by the autocorrelation matrix calculating means;
Arriving wave number estimating means (130) for estimating the number of incoming waves based on the eigenvalue (λ) calculated by the eigenvalue calculating means;
Based on the beat signal, the distance and relative speed of the target are obtained, and history information storage means for storing them as history information is provided.
The arrival wave number estimation means includes target position prediction means (400) for predicting the position of the target at the time of current arrival wave estimation from the history information stored in the history information storage means, and the target position A radar which predicts whether or not a plurality of targets are arranged from the target positions predicted by a prediction means, and estimates the number of incoming waves based on the prediction result apparatus.   The arrival wave number estimation means obtains the number of targets predicted to be arranged in the current arrival wave estimation from the target position predicted by the target position prediction means, and this number and the previous arrival wave estimation The difference between the number of targets lined up at the time is the difference between the number of incoming waves estimated during the previous arrival wave estimation and the number of arrival waves estimated during the current arrival wave estimation. Is not equal to the number of incoming waves estimated during the previous arrival wave estimation, the number of targets predicted to be aligned during the current arrival wave estimation and the previous arrival wave estimation The radar according to claim 1, wherein the number of the incoming waves is estimated by adding or subtracting a difference from the number of the targets arranged in the case of the incoming wave estimation. apparatus. A transmission signal is transmitted through the transmission antenna (4), and a plurality of incoming waves arriving from a plurality of directions are received via a plurality of antennas (5a) arranged at different positions, and a reception signal for each antenna is received. From the radar apparatus for estimating the direction of the incoming wave from the target reflecting the transmission signal,
Beat signal generating means (6) for generating a beat signal which is a frequency component of a difference between the transmission signal and the reception signal;
Autocorrelation matrix calculating means (110) for calculating an autocorrelation matrix (Rxx) based on the beat signal;
Eigenvalue calculating means (120) for calculating the eigenvalue (λ) from the autocorrelation matrix calculated by the autocorrelation matrix calculating means;
Arriving wave number estimating means (130) for estimating the number of incoming waves based on the eigenvalue (λ) calculated by the eigenvalue calculating means;
Based on the beat signal, the distance and relative speed of the target are obtained, and history information storage means for storing them as history information,
The arrival wave number estimating means includes threshold setting means (200, 210) for setting a threshold (λTH) of the eigenvalue (λ), and the eigenvalue is based on the threshold (λTH) set by the threshold setting means. (Λ) is divided into eigenvalues (λ1 to λL) of the signal space and eigenvalues (λL + 1 to λLK) of the noise space to estimate the number of incoming waves, and the history information stored in the history information storage means To target position prediction means (400) for predicting the position of the target at the time of current arrival wave estimation, and whether or not a plurality of the targets are arranged from the target positions predicted by the target position prediction means. Of the threshold (λ) set by the threshold setting means based on the prediction result. Radar apparatus, characterized by being adapted to adjust.

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