JP4972852B2 - Radar equipment - Google Patents

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JP4972852B2
JP4972852B2 JP2003359149A JP2003359149A JP4972852B2 JP 4972852 B2 JP4972852 B2 JP 4972852B2 JP 2003359149 A JP2003359149 A JP 2003359149A JP 2003359149 A JP2003359149 A JP 2003359149A JP 4972852 B2 JP4972852 B2 JP 4972852B2
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敬之 稲葉
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三菱電機株式会社
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  The present invention relates to a radar apparatus, and more particularly to a technique for measuring an angle by suppressing an interference wave.

  In a radar device equipped with an array antenna such as a phased array, a sum (Σ) signal and a difference (Δ) signal are calculated from the output of each antenna element and normalized with the Σ signal in order to obtain the direction in which the measurement target exists. In many cases, a monopulse angle measurement method for obtaining an angle from a Δ signal is used. However, when an array antenna is adopted for an on-vehicle radar, the monopulse angle measurement method cannot be used in many cases. This is a monopulse angle measurement method that measures the angle of a single target. Since the environment in which on-vehicle radar is used is on the road, the radar waves emitted by the vehicle's radar device can vary in various distances. It is reflected by a vehicle having a speed and a direction of motion, and a situation in which a plurality of vehicles exist in the same beam often occurs, and a correct angle measurement value cannot be obtained.

  In such a case, MUSIC (MUltiple SIgnal Classification) method, ESPRIT (Estimation via Rotational Invariant Technique) method or ML (Maximum Likelihood) method known as super-resolution angle measurement method is used. These super-resolution angle measurement methods can resolve the incoming waves contained in the same beam in principle, but the power difference between the incoming waves is large, the angle difference is small, and When a sufficient number of data samples (called the number of snapshots) cannot be obtained, accuracy is often not obtained. For example, an on-vehicle radar is also mounted on the oncoming vehicle, and the radar wave (direct wave) radiated to the vehicle by the radar is a radar wave (reflected wave) radiated from the vehicle-mounted radar of the own vehicle and reflected to the target. Power is stronger than. In such a situation, since the power difference between the incoming waves is large, angle separation is difficult only by the super-resolution angle measurement method.

  The following method has been proposed as a solution to such a problem. That is, first, the transmission of the own vehicle radar wave is temporarily interrupted, and the data of only the interference wave is measured during that time. Then, an eigenvector of the correlation matrix of the interference wave is obtained, and a projection matrix for projecting (orthogonal transformation, OP; Orthogonal Projection) to a space orthogonal to the interference wave eigenspace spanned by the eigenvector is calculated. Further, by performing projective transformation using an orthogonal transformation projection matrix, a data vector in which interference waves are suppressed is obtained, and the super-resolution angle measurement method is applied using this data vector (for example, non-patent) Reference 1).

T.A. Nohara, P.A. Weber and A.M. Premiji, "Adaptive Mainbeam Jamming Suppression for Multi-function Readers," IEEE National Rader conference, Dallas, TX, pp. 207-212, May, 1998.

  The conventional method based on the orthogonal transformation projection matrix has a problem that the calculation load increases because it is necessary to perform eigen expansion of interference waves and obtain eigen vectors. The present invention has been made to solve such problems, and has an object to effectively measure a target angle in a situation where a slight angle difference exists such that an interference wave and a target exist in the same beam. It is said.

The radar apparatus according to the present invention includes an array antenna that receives a reflected wave from a measurement target and outputs a reception vector, and a correlation between a data vector of an interference wave received by the array antenna in a time zone during which no radar wave is transmitted. An interference wave number estimating means for obtaining eigenvalues of the matrix and estimating the number of found eigenvalues as the number K of interference waves, and suppressing interference waves included in the received vector using monopulse angle measurement when K = 1. An interference wave suppressing means for suppressing the interference wave included in the received vector based on the eigenvalue of the correlation matrix obtained by the interference wave number estimating means when K> 1, and outputting the data vector; and the interference wave suppressing means Target angle estimating means for calculating the arrival direction of the reflected wave to be measured by applying a super-resolution angle measurement method to the data vector outputted by

The present invention radar apparatus according to the, interference wave number was to perform the monopulse angle measurement in the case of one, it is possible that the calculation of the eigenvectors reduce the calculation amount becomes unnecessary interference when the wave number is greater than 1 For the eigenvalue of the correlation matrix used for interference wave suppression, the value calculated at the time of estimating the number of interference waves may be used, so that the amount of calculation does not increase .

Embodiments of the present invention will be described below with reference to the drawings.
Embodiment 1 FIG.
1 is a block diagram showing a configuration of a radar apparatus according to Embodiment 1 of the present invention. In the figure, an array antenna 1 is an array antenna element that receives a radar wave. The reception power monitor 2 is a part for determining whether or not the array antenna 1 receives an interference wave, and outputs a received data vector (hereinafter simply referred to as a reception vector) when receiving the interference wave. It has a switch. In addition, in the above and the following description, the term “part” means that it is configured by an element or a circuit, and a general DSP (Digital Signal Processor) or CPU (Central Processing Unit) is combined with a computer program, This includes cases where functions are configured.

  The interference wave correlation matrix estimator 3 is a part that obtains an estimated value of the correlation matrix from the measured interference wave reception vector. The interference wave number estimator 4 performs eigenexpansion of the correlation matrix of the interference wave estimated by the interference wave correlation matrix estimator 3, obtains an eigenvalue, and calculates the number of eigenvalues larger than the eigenvalue of noise as the number of interference waves. It is a part. When the interference wave number calculated by the interference wave number estimator 4 (the interference wave number is K in FIG. 1) is 2 or more, the interference wave eigenvector estimator 5 is an eigenvector (that is, an interference wave) corresponding to the eigenvalue of the correlation matrix. This is a part for calculating an eigenvector. The orthogonal transformation matrix calculator 6 is a part that calculates an orthogonal transformation matrix from the interference wave eigenvector.

  The monopulse angle estimator 7 is a part that estimates the arrival angle of the interference wave when the interference wave number calculated by the interference wave number estimator 4 is 1 (K = 1). The blocking matrix calculator 8 is a part that calculates a blocking matrix for suppressing the interference wave from the angle estimated by the monopulse angle estimation device 7.

  The projective converter 9 is a part that performs projective transformation on the received vector. The matrix used for the projective transformation is a blocking matrix when K = 1, that is, the interference wave number is 1, and is an orthogonal transformation projection matrix when K> 1, ie, the interference wave number is 2 or more. The target angle estimator 10 includes a data vector having a dimension of the number of array elements that has undergone projective transformation by the projective transformer 7 and suppresses interference waves, and a blocking matrix (when K = 1) or an orthogonal transformation matrix (K> 1). In this case, the target angle is estimated by super resolution angle measurement such as MUSIC method or ML method.

  Next, the operation of the radar apparatus according to Embodiment 1 of the present invention will be described. The reception power monitor 2 determines that an interference wave is incident when a signal different from the transmission wave transmitted by itself is incident on the array antenna 1, and measures the reception signal of only the interference wave. Specifically, for example, it is determined that an interference wave is received when the received signal received is larger than the internal noise in a time zone during which no radar wave is transmitted. When it is determined that the received power monitor 2 is receiving an interference wave, the received power monitor 2 connects the switch provided therein to the output terminal, and outputs the received vector received by the array antenna 1 to the interference wave correlation matrix estimator 3.

The interference wave correlation matrix estimator 3 estimates the correlation matrix R by taking the average of all snapshots of the measured reception vector. When the reception vector is X (t) and the complex conjugate of the reception vector is X (t) H , the correlation matrix R is given by equation (1).
In the formula (1), <*> means an average operation of *.

Next, the interference wave number estimator 4 performs eigenexpansion of the correlation matrix R to obtain a plurality of eigenvalues. Also, the number of eigenvalues that are larger than the noise eigenvalue σ 2 is obtained, this number is estimated as the number K of interference waves, and the interference wave number K and the eigenvalue of the correlation matrix of the interference waves are output.

  In the case of K> 1, the interference wave eigenvector estimator 5 calculates an eigenvector (that is, an interference wave eigenvector) for the eigenvalue of the correlation matrix of the interference wave calculated by the interference wave number estimator 4. The orthogonal transformation matrix calculator 6 subtracts the interference wave eigenspace spanned by the interference wave eigenvector from the unit matrix to calculate an orthogonal transformation matrix. In the following description, this orthogonal transformation matrix is assumed to be P.

  The projective transformer 9 performs projective transformation by multiplying the received vector X (t) by the previously obtained orthogonal transform projection matrix P from the left. As a result, a data vector having dimensions corresponding to the number of array elements in which interference waves are suppressed is obtained as a signal after projective transformation. As described above, the output signal does not become one channel as in the case of normal null beam forming, and the target angle exceeding the beam width can be estimated by performing the projective transformation while having the dimensions corresponding to the number of array elements. It becomes.

  Subsequently, the target angle estimator 10 acquires a data vector having the dimension of the number of array elements in which the interference wave is suppressed by projective transformation. Then, using the orthogonal transformation matrix P, projective transformation is performed on the array mode vector (A) used for angle measurement in the same manner as the received vector, and a new array mode vector (B is set, ie B = PA). Using this array mode vector B, target angle estimation is performed by a super-resolution angle measurement method such as the MUSIC method or the ML method. In this way, when the MUSIC method or the ML method is used alone, even if the angle cannot be separated, the target angle existing in the same beam as the interference wave is suppressed by suppressing the interference wave by projective transformation. Is possible.

On the other hand, in the case of K = 1, in the monopulse angle estimator 7, first, in a plurality of required directing directions θ m (m = 1, 2,..., M, M are the number of beams) in the coverage. On the other hand, the sum beam Σ m (t) and the difference beam Δ m (t) are calculated by the equation (2).
In Equation (2), N is the number of elements in the array antenna 1. Further, a (θ) is an array mode vector, and in the case of a linear array in which the element antenna intervals are equal intervals d,
It is. T represents a transposed matrix, and λ is a wavelength. Here, for example, intervals of theta m is used -3dB beamwidth spacing.

The beam direction θ m where the interference wave exists is calculated from the amplitude level of the multi-beam sum signal Σ (t), and the ratio α is obtained from the Σ m (t) and Σ m (t) by the equation (4). .
Is calculated. Next, a function of the beam directing direction θ m and the error angle Δθ previously obtained in the antenna manufacturing stage
Using,
From the angle θ i of the interference wave. Here, the subscript i is an acronym for interference representing interference, and is used to emphasize that θ i is the angle of the interference wave.

The blocking matrix calculator 8 calculates a projection matrix P BM represented by the array mode vector a (θ i ) from the interference wave angle θ i using Expression (7). This projection matrix P BM is called a blocking matrix (BM).

In the blocking matrix, when the array mode vector is expressed by Equation (3), a (θ i ) H a (θ i ) = N regardless of the arrival direction θ i of the interference wave, and almost a (θ A projection matrix can be obtained only by calculating i ) a (θ i ) H. In the blocking matrix, deeper nulls can be formed in the interference wave direction than the orthogonal transformation matrix.

Next, the projective converter 9 obtains the received vector X (t) from the array antenna 1 and performs projective transformation using the blocking matrix P BM . That is, if the converted data vector is Y (t),
It becomes.

The data vector Y (t) calculated by the equation (8) is a data vector having a dimension of the number of array elements in which interference waves are suppressed. The target angle estimator 10 acquires the data vector Y (t), and further acquires the blocking matrix P BM used for the projective transformation from the blocking matrix calculator 8. Projection transformation is similarly performed on the array mode vector A to calculate a new array mode vector B BM (= P BM A). Then, the array mode vector B BM is adopted as a mode vector, and the target angle of the measurement target is calculated by, for example, a super resolution angle measurement method such as the MUSIC method or the ML method, or a monopulse angle measurement method.

As is apparent from the above, according to the radar apparatus of the first embodiment of the present invention, the calculation of eigenvectors becomes unnecessary by using a blocking matrix instead of an orthogonal transformation matrix as a projection matrix. Further, since the calculation of the blocking matrix can be performed only by calculating a (θ i ) a (θ i ) H as described above, the calculation amount can be reduced also in this respect.

  Further, in the process of calculating the blocking matrix, the arrival direction of the interference wave is also obtained by the monopulse angle estimator 7. Therefore, even when the MUSIC method or ML method is used alone, the angle of the interference wave is obtained even if the target angle cannot be estimated, and the interference wave is suppressed by projective transformation using a blocking matrix. The target angle can be measured.

Embodiment 2. FIG.
The radar apparatus according to Embodiment 1 estimates the target angle by efficiently suppressing the interference wave using the monopulse angle estimation method and the blocking matrix when the interference wave number is 1 (K = 1). there were. On the other hand, when the interference wave number is larger than 1 (K> 2), even if the interference wave-to-internal noise ratio (S / I) is small, a projection matrix is used that provides good interference suppression performance. Thus, the interference wave may be suppressed. The radar apparatus according to Embodiment 2 of the present invention has such features.

  FIG. 2 is a block diagram showing a configuration of a radar apparatus according to Embodiment 2 of the present invention. In the figure, an MSN matrix calculator 11 is a part that calculates an inverse matrix of a correlation matrix. The other components having the same reference numerals as those in FIG. 1 are the same as those in the first embodiment, and thus the description thereof is omitted.

  Next, the operation of the radar apparatus according to Embodiment 2 of the present invention will be described. Similarly to the radar apparatus according to the first embodiment, the reception power monitor 2 determines the presence or absence of an interference wave, and further passes through the interference wave correlation matrix estimator 3 and the interference wave number estimator 4 in the second embodiment of the present invention. The radar apparatus estimates the number of interference waves. Here, only the case where the number (K) of interference waves is 2 or more (K> 2) will be described.

When K> 1, the interference wave eigenvector estimator 5 estimates the angle of the interference wave using an angle measurement method using eigenexpansion, for example, the MUSIC method. In the MUSIC method, a noise space E = [e 1 which is composed of eigenvectors e n (n = 1, 2,..., N−K) corresponding to eigenvalues of noise from eigenvalues of correlation matrix R of interference waves obtained by wave number estimation. e 2 ... e N−K ]. N is the number of elements.

Next, the MSN matrix calculator 11 calculates an inverse matrix P MSN (= R −1 ) of the correlation matrix R. Correlation matrix R, using the interference wave eigenvectors e n calculated by the interference wave eigenvector estimator 5,
It is expressed as eigendevelopment. Here, σ n 2 is a noise variance value, and λ k is an eigenvalue of the k-th interference wave. The variance value of the noise is the average of the eigenvalues of the noise,
From calculated, the average value sigma 2 Distant, using official inverse matrix when P MSN is
It becomes.

The PMSN obtained here is the inverse of the correlation matrix shown by the equation (12) used in obtaining the weight vector w from the mode vector v = a (θ) for the desired direction θ in the MSN (Maximum Signal to Noise ratio) method. Matrix R- 1 .

When the correlation matrix R of the interference wave fluctuates, the recurrence formula is set with R −1 obtained by the equation (11) as an initial value.
From this, R -1 can be obtained step by step. In Expression (13), q is a subscript indicating the order of the recurrence formula (for example, the q-th sample), and β is a constant that satisfies 0 <β <1. Xq is a received vector in the q-th sample, for example.

When the eigenvalue λ k >> σ 2 of the interference wave (when the eigenvalue of the interference wave is sufficiently larger than the noise dispersion value)
As a result, Equation (11) is an orthogonal transformation (OP) matrix used in Non-Patent Document 1.
Is approximated by

  The projective transformer 9 performs projective transformation on the received vector X (t) using the inverse matrix of the correlation matrix instead of the orthogonal transform matrix, and calculates the data vector Y (t) by the equation (8). The target angle estimator 10 then estimates and outputs the target angle using the array mode vector calculated by the MSN matrix calculator 11.

  As is apparent from the above, according to the radar apparatus of the second embodiment of the present invention, the correlation at which the input / output S / N ratio is maximized even when the interference wave is not sufficiently larger than the noise (internal noise). Interference wave suppression can be performed by projective transformation of the received vector using the inverse matrix.

  Furthermore, since the eigenvalue required for calculating the inverse matrix of the correlation matrix may be the one calculated at the time of estimating the wave number of the interference wave, the amount of calculation does not increase compared to the case where the orthogonal transformation matrix is used.

Embodiment 3 FIG.
In the radar apparatus according to the first and second embodiments, interference waves can be suppressed. However, in order to obtain a target angle, it is necessary to perform an estimation calculation of the target angle at all time samples. It has become. Therefore, in order to solve this problem, a multi-beam may be formed from the antenna element data subjected to the projective transformation, and angle estimation may be performed by limiting the range to the target beam direction. The radar apparatus according to Embodiment 3 of the present invention has such a feature.

  FIG. 3 is a block diagram showing a configuration of a radar apparatus according to Embodiment 3 of the present invention. In the figure, a multi-beam former 12 is a part that performs multi-beam formation from a data vector. The pulse compressor 13 is a part that performs pulse compression for each beam that has been formed into a multi-beam. The target detector 14 is a part that performs target detection only for each beam formed by multi-beams, and the search range limited target angle estimator 15 limits the delay time including the target and performs angle estimation. This is the part to be performed. In addition, about the other component which attached | subjected the code | symbol same as FIG. 2, since it is the same as that of Embodiment 2, description is abbreviate | omitted.

  Next, the operation of the radar apparatus according to Embodiment 3 of the present invention will be described with reference to the drawings. Also in this radar apparatus, the array antenna 1, the reception power monitor 2, the interference wave correlation matrix estimator 3, the interference wave number estimator 4, the interference wave eigenvector estimator 5, the monopulse angle estimator 7, the blocking matrix calculator 8, the projection The operation of converter 9 operates in the same manner as in the second embodiment. Therefore, for example, the projective converter 9 performs projective transformation on the received vector X (t) and outputs a data vector Y (t), and the MSN matrix calculator 11 calculates an inverse matrix of the correlation matrix.

Therefore, the multi-beamformer 12 uses the data vector Y (t) to change the steering vector in the θ m direction to v m (= a (θ m )) (m = 1, 2, ..., M, where M is the number of beams)
Multi-beam formation is performed by When the projection matrix P of Expression (8) is P MSN , Expression (16) becomes the MSN beam described in the second embodiment. The output Z m (t) is a measurement data vector continuous in the distance direction for each beam.

Next, the pulse compressor 13 performs pulse compression on the data vector Z m (t) (here, the transmission wave is a PN code signal) obtained by Expression (16) for each beam. As a result, the pulse compressor 13 compresses the target reflection into a distance sample corresponding to one chip width (one binary phase time width). Here, it is assumed that the pulse-compressed data vector is Z pm (t) (m = 1, 2,..., M). Subsequently, the target detector 14 performs threshold processing on the data vector Z pm (t) for each beam that has been pulse-compressed in the distance direction. And consequently performing target detection, obtain the target delay time t s. Thus, the beam direction includes the target v m and the distance R (= 2t s / c) is obtained.

On the other hand, the search range-limited target angle estimator 15 obtains the beam direction obtained by the target detector 14 v m and the delay time t s, includes the target time samples performed the target angle estimate restricted to the delay time t s, and the angle estimation using the MUSIC method or ML method, performs angle estimation limit its search range in the beam direction v m that contains target.

  As is apparent from the above, according to the radar apparatus of the third embodiment of the present invention, the S / N is improved and target detection is performed by performing multi-beam formation and pulse compression from the projection-transformed data vector. As a result, target time delay (ie, distance) can be obtained, and target angle estimation does not need to be performed for all time samples and the required angle range, reducing the amount of calculation for target angle estimation. It becomes.

Depending on the conditions such as the beam width and the required coverage, the beam is sequentially formed by the equation (10) using the weight vector w m (= Pv m ), and the target is detected from the threshold processing in the distance direction. only, it may be performed projective transformation by the formula (8) with respect to the data vector X of the delay time t s (t s) when. By doing so, the amount of calculation can be further reduced.

Embodiment 4 FIG.
In the first to third embodiments, the radar wave radiated from the radar device of the oncoming vehicle is mainly assumed as the interference wave. However, in an actual use environment, the own transmitted wave is reflected on the road surface or the like, and as a result, it may enter the radar antenna as an unnecessary reflected wave (clutter). In such a case, a filter bank is formed by pulse Doppler filter processing that performs FFT processing in the pulse direction for each distance (time sample), and a pulse corresponding to the Doppler frequency of the road surface reflection clutter expected from its own speed. Only a filter other than the Doppler filter may be selected. The radar apparatus according to Embodiment 4 of the present invention has such a feature.

  4 is a block diagram showing a configuration of a radar apparatus according to Embodiment 4 of the present invention. In the figure, a pulse Doppler filter 16 is a part that performs fast Fourier transform on the data vector Y (t) in the pulse direction. The pulse Doppler filter selector 17 is a part that selects a filter that does not include clutter from a plurality of pulse Doppler filter banks. In addition, about the other component which attached | subjected the code | symbol same as FIG. 3, since it is the same as that of Embodiment 3, description is abbreviate | omitted.

  Next, the operation of the radar apparatus according to Embodiment 4 of the present invention will be described with reference to the drawings. Also in this radar apparatus, the array antenna 1, the reception power monitor 2, the interference wave correlation matrix estimator 3, the interference wave number estimator 4, the interference wave eigenvector estimator 5, the monopulse angle estimator 7, the blocking matrix calculator 8, the projection The operation of converter 9 operates in the same manner as in the third embodiment. Therefore, for example, the projective converter 9 performs projective transformation on the received vector X (t) and outputs a data vector Y (t).

  When the projecting transformer 9 outputs the data vector Y (t), the pulse Doppler filter 16 performs fast Fourier transform on the projecting transformed data vector Y (t) in the pulse direction. The Doppler frequency of the clutter can be regarded as a known amount depending on its own speed. Therefore, the pulse Doppler filter selector 17 selects a filter that does not include clutter from the pulse Doppler filter bank. This is done by comparing the power of the received vector with the internal noise power. The selected pulse Doppler filter does not include clutter but only internal noise.

  Subsequently, the multi-beamformer 12 performs multi-beam formation for each selected filter. In this way, the multi-beamformer 12 outputs a data vector in the time direction defined by the beam direction and the pulse Doppler filter number. The pulse compressor 13 pulse-compresses the data vector, and the target detector 14 performs threshold processing in the distance direction on the pulse-compressed data vector to detect the target.

In this way, the target detector 14 obtains the beam direction v m in which the target is included, the distance R (= 2t s / c), and the pulse Doppler filter number. Search range-limited target angle estimator 15, the target is using a data vector at delay time t s of the detected pulse Doppler filter number, performs angle estimation target has limited the scope to the detected beam direction v m .

  As is apparent from the above, according to the radar apparatus of the fourth embodiment of the present invention, when a transmission wave by itself is reflected on the road surface or the like and is incident on the radar antenna as clutter, by combining the pulse Doppler filter, And the target distance, Doppler frequency, and angle can be obtained.

  The radar apparatus according to the present invention can be used as, for example, a radar apparatus for in-vehicle use.

It is a block diagram which shows the structure of the radar apparatus by Embodiment 1 of this invention. It is a block diagram which shows the structure of the radar apparatus by Embodiment 2 of this invention. It is a block diagram which shows the structure of the radar apparatus by Embodiment 3 of this invention. It is a block diagram which shows the structure of the radar apparatus by Embodiment 4 of this invention.

Explanation of symbols

1 array antenna,
2 Received power monitor,
3 interference wave correlation matrix estimator,
4 Interference wave number estimator,
5 interference wave eigenvector estimator,
6 Orthogonal transformation matrix calculator,
7 Monopulse angle estimator,
8 Blocking matrix calculator,
9 Projection converter,
10 Target angle estimator,
11 MSN matrix calculator,
12 Multi-beamformer,
13 Pulse compressor,
14 target detector,
15 Search range limited type target angle estimator,
16 Pulse Doppler filter,
17 Pulse Doppler filter selector.

Claims (4)

  1. An array antenna that receives a reflected wave from a measurement object and outputs a reception vector;
    Interference wave number estimating means for obtaining eigenvalues of a correlation matrix for a data vector of interference waves received by the array antenna in a time zone during which no radar wave is transmitted, and estimating the number of the obtained eigenvalues as the number K of interference waves;
    When K = 1, the interference wave included in the reception vector is suppressed using a monopulse angle measurement method. When K> 1, the reception vector is determined based on the eigenvalue of the correlation matrix obtained by the interference wave number estimation means. Interference wave suppressing means for suppressing the including interference wave and outputting the data vector;
    Target angle estimation means for calculating the arrival direction of the reflected wave of the measurement object by applying a super-resolution angle measurement method to the data vector output by the interference wave suppression means;
    Radar equipment, characterized in that it comprises a.
  2. The interference wave suppressing means suppresses the interference wave included in the received vector using a monopulse angle measurement method when K = 1, and the eigenvalue of the correlation matrix obtained by the interference wave number estimating means when K> 1. radar equipment according to claim 1, characterized in that the output data vector by suppressing the interference wave included in the received vector based on the inverse matrix of the calculated correlation matrix from.
  3. Multi-beam forming means for forming a multi-beam from the data vector output by the interference wave suppressing means;
    Pulse compression means for pulse-compressing the data vector for each beam formed by the multi-beam forming means;
    Target detection means for performing target detection from the data vector pulse-compressed by the pulse compression means,
    The radar apparatus according to claim 2, wherein the target angle estimation unit performs target angle calculation limited to a range of a beam in which the target detection unit detects a target.
  4. A pulse Doppler filter that analyzes the frequency of the data vector output by the interference wave suppression means for each antenna element;
    Pulse Doppler selection means for selecting a data vector not including clutter from the data vector based on a result of frequency analysis performed by the pulse Doppler filter, and
    4. The radar apparatus according to claim 3, wherein the multi-beam forming unit forms a multi-beam from the data vector selected by the pulse Doppler selecting unit.
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