JP6367140B2 - Radar apparatus and radar signal processing method - Google Patents

Description

  The present embodiment relates to a radar apparatus and a radar signal processing method.

  In a conventional radar apparatus, when detecting a small target in an unnecessary wave environment such as thermal noise or clutter, generally, CFAR (Constant False Alarm Rate) processing is often used for clutter suppression. However, in the CFAR processing, when detecting a small target, the amplitude intensity of the small target does not exceed the threshold of the CFAR and may not be detected. Further, when the main lobe faces the ground surface, the sea surface, etc., there is a problem that the fixed clutter is received and the detection performance deteriorates.

Pulse compression, Ouchi, “Basics of Synthetic Aperture Radar for Remote Sensing”, Tokyo Denki University Press, pp.131-149 (2003) CFAR (Constant False Alarm Rate), Yoshida, "Revised Radar Technology", IEICE, pp.87-89 (1996) Phase monopulse angle measurement, Yoshida, 'Revised radar technology', IEICE, pp.260-264 (1996) Optical Flow, Tamura, 'Computer Image Processing', Ohmsha, pp.245-247 (2002) MPRF, Guy Morris, ‘AIRBORNE PULSE DOPPLER RADAR 2nd edition’, pp.264-270 (1996)

  As described above, in the conventional radar apparatus, when CFAR (Constant False Alarm Rate) processing is adopted for clutter suppression, the signal strength is small when detecting a small target with a small RCS (Radar Cross Section). In some cases, the threshold was not exceeded and it was not detected. Further, when the main lobe faces the ground surface, the sea surface, etc., there is a problem that the fixed clutter component cannot be suppressed and the detection performance deteriorates.

  The present embodiment has been made in view of the above problems, and exhibits a high detection capability that enables detection of a target having a small RCS (Radar Cross Section) that cannot be detected by CFAR or the like under an unnecessary environment such as clutter. An object of the present invention is to provide a radar apparatus capable of performing the same and a radar signal processing method thereof.

  In order to solve the above-described problems, the present embodiment transmits and receives N (N> 1) pulses in an arbitrary direction, and in a radar apparatus that detects a target from the received signal, the received signal of the pulse is converted to PRI. The frequency domain is converted to the frequency domain, and FR data is acquired from the received signal converted to the frequency domain by shifting the time by P (P ≧ 2) times, and an optical flow diagram and amplitude intensity are obtained from the FR data for the P times. A figure is created, a feature quantity based on the velocity vector and the amplitude intensity is calculated based on the optical flow diagram and the amplitude intensity diagram, and when the feature quantity exceeds a predetermined threshold, it is detected as a target.

1 is a block diagram showing a configuration of a radar apparatus according to a first embodiment. The conceptual diagram which shows the flow of the target detection in the radar signal processing of the radar apparatus shown in FIG. The wave form diagram for demonstrating the target distance measuring method of the radar apparatus shown in FIG. The wave form diagram for demonstrating the target speed measuring method of the radar apparatus shown in FIG. The block diagram which shows the structure of the radar apparatus which concerns on 2nd Embodiment. The conceptual diagram which shows the flow of the target detection in the radar signal processing of the radar apparatus shown in FIG. The block diagram which shows the structure of the radar apparatus which concerns on 3rd Embodiment. The conceptual diagram for demonstrating the high resolution in the radar signal processing of the radar apparatus shown in FIG. The block diagram which shows the structure of the radar apparatus which concerns on 4th Embodiment. The conceptual diagram for demonstrating the high resolution and the stretch in the radar signal processing of the radar apparatus shown in FIG.

  Hereinafter, embodiments will be described with reference to the drawings. In the description of each embodiment, the same portions are denoted by the same reference numerals, and redundant description is omitted.

(First embodiment)
Hereinafter, the radar apparatus according to the first embodiment will be described with reference to FIGS. 1 to 4.

  FIG. 1 is a block diagram showing the configuration of the radar apparatus according to the first embodiment. In the radar apparatus shown in FIG. 1, the antenna 1 is a phased array antenna formed by arranging a plurality of antenna elements to form a large aperture array. The antenna 1 is repeatedly supplied from the transmitting / receiving unit 21 of the transmitter / receiver 2 at a specific cycle. A transmission pulse signal having a frequency (hereinafter referred to as a PRF (Pulse Repetition Frequency) signal) is transmitted in a specified direction and the reflected wave is received. The transceiver 2 forms a received beam in an arbitrary direction by performing phase control on the signals received by the plurality of antenna elements of the antenna 1 in the transceiver unit 21 according to instructions from the beam controller 22 and combining them. To obtain a PRF received signal. Here, the beam control unit 22 performs phase control corresponding to each beam on the transmission / reception unit 21 so as to form a Σ beam and a Δ beam based on the angle measurement value in the designated target direction. As a result, the transmission / reception unit 21 generates a Σ signal and a Δ signal and outputs them to the signal processor 3.

  The Σ signal and Δ signal input to the signal processor 3 are converted into digital signals for each system by AD (Analog-Digital) converters A11 and B11 in each system, and then the range axis Fourier transform unit (FFTx ) Sent to A12 and B12. The range axis Fourier transform units (FFTx) A12 and B12 convert the input Σ signal and Δ signal into a frequency domain signal along the range axis by performing Fourier transform on the time axis. Range reference signal multipliers A13 and B13 perform pulse compression by multiplying the frequency domain signals of the range axes of the Σ signal and Δ signal by a reference signal for range compression. Inverse Fourier transform units (IFFTx) A14 and B14 perform inverse Fourier transform on the frequency domain Σ signal and Δ signal multiplied by the range reference signal to return them to the time domain signal. PRI (Pulse Repetition Interval) axis Fourier transform units (FFTy) A15 and B15 convert the Σ signal and Δ signal returned to the time domain into frequency domain signals on the PRI axis. Note that the order of FFTx and FFTy may be reversed.

The pulse compression by the reference signal is formulated as follows in the case of linear chirp, for example (see Non-Patent Document 1). Pulse compression is a correlation process between an input signal and a reference signal for range compression, and is performed in the frequency domain.

The output fp of the pulse compression can be calculated by IFFT related to the ω axis of fcs.

Using this, FFTy processing is performed on the PRI axis to obtain a signal fcs (t, fd).

The relationship between time and range is:

  Subsequently, the FR data storage units A16 and B16 respectively process the Σ signal and Δ signal that have been subjected to FFTx processing and FFTy processing for Doppler-range axis data (hereinafter referred to as FR data) for processing by a plurality of coherent processing intervals (CPI). ). An example of FR data stored for CPI processing is shown in FIG. Here, a state is shown in which FR data is acquired P times (P ≧ 2) by shifting the time.

  Here, in the Σ system, the amplitude intensity calculation unit A17 calculates the absolute value of the amplitude intensity for the FR data stored in the FR data storage unit A16. The optical flow processing unit A18 creates an amplitude intensity diagram and an optical flow diagram (see Non-Patent Document 4) using the FR data based on a plurality of CPI signals stored in the FR data storage unit A16. The optical flow diagram creates an amplitude strength diagram of a plurality of FR data having different times (generally using image amplitude strength data, and in the case of radar, FR data for each CPI). It is the vector distribution figure which calculated | required the movement amount and calculated the velocity vector from the movement amount. An example of an amplitude intensity diagram for each CPI is shown in FIG. 2B, and an optical flow diagram is shown in FIG. In the case of FR data, since the two-dimensional display is the Doppler range axis, the Doppler axis represents a change in the relative speed between the target and the radar, the range axis represents a change in the relative distance between the target and the radar, and both changes are expressed as a velocity vector. Call.

  The feature quantity extraction unit A19 extracts the feature quantity of the velocity vector created by the above optical flow. In other words, thermal noise has a velocity vector oriented in a random direction, and clutter also has a large intensity change at each reflection point compared to the target, making it difficult to align the velocity vectors. On the other hand, the target is a rigid body, the reflection point fluctuations are relatively small even at different times, and the velocity vectors are easily aligned. Therefore, by using the characteristics of both, the feature quantity of the velocity vector can be extracted from the optical flow.

  Specifically, in the feature amount extraction unit A19, at least one of the FR data of the plurality of CPIs, the maximum value or the average value of the amplitude intensity of the plurality of FR data, or the like is used. Cells Cell (n) (n = 1 to N) that are equal to or higher than the threshold are extracted. An example of the cell signal extraction result based on the amplitude intensity is shown in FIG. In addition, centering on Cell (n), it extracts the velocity vector in the cell of the predetermined gate range Cell-gate (n) (n = 1 to N), and features the maximum or average value of the velocity vector as the feature quantity. Output as. An example of velocity vector extraction is shown in FIG. The target detection unit A20 outputs a target detection result when the value of the feature amount extracted by the feature amount extraction unit A19 exceeds a predetermined threshold. An example of the target detection result is shown in FIG.

  Here, the target detection result of the target detection unit A20 is sent to the cell detection unit B17. The cell detection unit B17 detects the FR data of the cell corresponding to the Σ-sequence target detection cell from the FR data stored in the Δ-sequence FR data storage unit B16.

  Next, the distance measurement / speed measurement processing unit A21 suppresses ambiguity by MPRF processing (see Non-Patent Document 5) using cell numbers of FR data of a plurality of CPIs having different PRIs obtained by the target detection unit A20. Perform resolver processing. As shown in FIG. 3, the target distance when there is ambiguity on the time axis (range axis) is to extract the ranges that have the same time (range) between multiple PRIs by arranging reflection points in multiple PRI directions. That's fine. As for speed measurement, as shown in FIG. 4, reflection points are arranged in a plurality of PRF directions, a Doppler having the same Doppler (speed) is extracted between the plurality of PRFs, and converted into a speed. This processing is performed on the two-dimensional surface of the range-Doppler axis, whereby the range and speed can be calculated simultaneously.

Next, the angle measurement method of the angle measurement processing unit A22 will be described. First, in the cell detection unit B17, a range-Doppler image is obtained from the output of the Δ beam (ΔAZ, ΔEL) of the antenna similarly to the Σ beam. Next, a Δ beam cell similar to the cell (range-Doppler axis cell) detected using the optical flow described above is extracted with the Σ beam, and an error voltage of the following equation is calculated.

  In the beam patterns of Σ and Δ, if the angle relationship obtained in advance is used as a table, the relationship between the reference error voltage εref and the angle is tabulated, ε is observed, and the angle is extracted by quoting the table. Is obtained. By performing similar processing for the AZ angle and the EL angle, angle measurement of both axes can be performed (see Non-Patent Document 3).

  As described above, according to the radar apparatus of the first embodiment, the Doppler range data (FR data) subjected to FFT processing on the PRI axis and pulse-compressed is shifted P times (P ≧ 2). An optical flow diagram and an amplitude intensity diagram are created from the P pieces of FR data, a feature quantity based on the velocity vector and the amplitude intensity is calculated, and a target is detected when a predetermined threshold is exceeded. In this way, by using the FR data that is the amplitude intensity of the Doppler range, using the plurality of reflection points of each target, an optical flow diagram and an amplitude intensity diagram are created, and a feature amount is extracted, so that clutter or the like is obtained. Even if the target has a small RCS that cannot be detected by CFAR or the like in the unnecessary environment, the target can be detected to obtain the distance, speed, and angle.

(Second Embodiment)
Hereinafter, a radar apparatus according to the second embodiment will be described with reference to FIGS. 5 and 6.

  FIG. 5 is a block diagram showing the configuration of the radar apparatus according to the second embodiment, and FIG. 6 is a conceptual diagram showing the flow of the processing. In FIG. 5, the same parts as those in FIG. 1 are denoted by the same reference numerals, and redundant description is omitted here.

  In the radar apparatus shown in FIG. 5, the difference from the first embodiment shown in FIG. 1 is that an adder A23 is interposed between the optical flow processor A18 and the feature quantity extractor A19 of the signal processor 3. There is. That is, in this embodiment, the optical flow processing unit A18 uses the FR data (FIG. 6A) by a plurality of CPI signals stored in the FR data storage unit A16 to use the amplitude intensity diagram (FIG. 6B). ) And an optical flow diagram (FIG. 6C) are created, and the addition unit A23 adds the amplitude intensity addition value Amp-sum (n) (n = 1 to N) in the Cell-gate (FIG. 6D )) And an addition vector Vel-sum (n) (n = 1 to N) (FIG. 6E) of the velocity vectors in the Cell-gate described above is obtained in the optical flow. It is assumed that the target detection unit A20 detects the target when both exceed the respective predetermined thresholds using the Amp-sum and Vel-sum as feature amounts.

  As described above, according to the second embodiment, the feature value is centered on the extreme value of the amplitude intensity diagram, and the absolute value of the added value of the amplitude intensity of the predetermined cell range and the added value of the velocity vector are respectively Target detection is performed when a predetermined threshold is exceeded. That is, by using the FR data that is the amplitude intensity of the Doppler range, an optical flow diagram and an amplitude intensity diagram are created using a plurality of reflection points of each target, and the velocity vector and amplitude intensity around the amplitude extreme value are generated. A feature value based on the added value is extracted. Thereby, even if the target has a small RCS that cannot be detected by CFAR or the like under an unnecessary environment such as clutter, the target can be detected and the distance, speed, and angle can be acquired.

(Third embodiment)
In the first embodiment, when the number of pulse hits is small, or when the frequency band is narrow and the range resolution is low, there may be a case where the number of cells of FR data is small and the velocity vector based on the optical flow cannot be calculated correctly. In the third embodiment, a method for increasing the number of cells of FR data is proposed as a countermeasure.

  Hereinafter, a radar apparatus according to the third embodiment will be described with reference to FIGS. 7 and 8.

  FIG. 7 is a block diagram showing the configuration of the radar apparatus according to the third embodiment, and FIG. 8 is a conceptual diagram showing the flow of the processing. In FIG. 7, the same parts as those in FIG. 1 are denoted by the same reference numerals, and redundant description is omitted here.

In the present embodiment, after the FFTy processing in each series of Σ signal and Δ signal, the FFTxy processing units A24 and B18 convert the signals into frequency domain signals by the Fourier transform of the range axis and the Doppler axis, and the zero padding units A25, In B19, zero padding is performed on the frequency axis, and IFFTxy processing units A26 and B20 convert the signal into a time domain signal by inverse Fourier transform on each of the range axis and the Doppler axis. The formulation is as follows.
First, the FR data

This is subjected to a two-dimensional IFFT to obtain a frequency-axis signal of the reference signal.

  If this FR_all is used as FR data (FIG. 8A) and the same processing as in the first embodiment is performed, as shown in FIG. 8B, the number of cells with high resolution around the extreme value is large. It is easy to extract the feature quantity of the amplitude intensity and the velocity vector of the optical flow, and the sensitivity of target detection is improved.

  As described above, according to the third embodiment, after the FR data is two-dimensionally FFTed, zero-padded on the two-dimensional axis, and the two-dimensional inverse FFT is performed again on the FR data of the first or second embodiment. Perform the form processing. In this case, even when the number of reflection points for each target is small, the number of reflection points can be increased by performing inverse FFT after zero filling of the frequency axis. The target detection performance can be improved.

(Fourth embodiment)
In the third embodiment, the method of increasing the number of cells by increasing the resolution of FR data by zero padding on the frequency axis has been described. In the zero padding method, the number of reflection points in the vicinity of the target reflection point increases, but the gap between the reflection points may increase at the center in the periphery of the extreme value in FIG. 8B, and the velocity vector cannot be calculated correctly. There is also sex. Therefore, in the fourth embodiment, a method of increasing the number of reflection points is proposed in view of the fact that the velocity vector based on the optical flow is easily calculated correctly when there are many reflection points.

  Hereinafter, a radar apparatus according to the fourth embodiment will be described with reference to FIGS. 9 and 10.

  FIG. 9 is a block diagram showing the configuration of the radar apparatus according to the fourth embodiment, and FIG. 10 is a conceptual diagram showing the flow of the processing. In FIG. 9, the same parts as those in FIG. 7 are denoted by the same reference numerals, and redundant description is omitted here.

  In the present embodiment, the FFTxy processing (A24, B18), zero padding (A25, B19), and IFFTxy processing (A26, B20) are applied to each of the Σ signal and Δ signal sequences, and then the stretch processing units A27, B21 are applied. The reflection points are stretched and output to the FR data storage units A16 and B16.

  The stretch processing units A27 and B21 extract extreme values exceeding a predetermined threshold in the amplitude intensity of FR data (FIG. 10A) (FIG. 10B). Centering on the extreme value, the amplitude intensity of a predetermined gate range is set to the same value as the maximum value or a value obtained by multiplying it by a coefficient (FIG. 10C).

  The zero padding process of the third embodiment is performed using the FR data obtained by stretching the maximum value. Note that the processing is not limited to the third embodiment, and only the processing of the first or second embodiment may be performed.

  Thus, according to the fourth embodiment, the FR data or the FR data is two-dimensionally FFTed, zero-padded on the two-dimensional axis, and then exceeds a predetermined threshold than the two-dimensional inverse FFT FR data. After the amplitude extreme value is extracted and replaced by an amplitude value obtained by multiplying a cell around the extreme value by a predetermined coefficient by the amplitude value of the extreme value, the process according to any of the first to third embodiments is performed. Thus, even when the number of reflection points for each target is small, the number of cells around the amplitude extreme value can be increased by the stretch process, and the feature quantity based on the amplitude intensity and the velocity vector can be extracted efficiently. Can be improved.

  The present embodiment is not limited to the above-described embodiment as it is, and can be embodied by modifying the components without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of components disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

DESCRIPTION OF SYMBOLS 1 ... Antenna, 2 ... Transmitter / receiver, 21 ... Transmitter / receiver, 22 ... Beam controller, 3 ... Signal processor, A11, B11 ... AD (Analog-Digital) converter, A12, B12 ... Range axis Fourier transform (FFTx) ), A13, B13... Range reference signal multiplication unit, A14, B14... Inverse Fourier transform unit (IFFTx), A15, B15... PRI (Pulse Repetition Interval) axis Fourier transform unit (FFTy), A16, B16. A17: Amplitude intensity calculation unit, A18: Optical flow processing unit, A19: Feature amount extraction unit, A20 ... Target detection unit, B17 ... Cell detection unit, A21 ... Ranging / speed measurement processing unit, A22 ... Angle measurement processing unit, A23: Adder, A24, B18 ... FFTxy processor, A25, B19 ... Zero padding, A26, B20 ... IFFTxy processor, A27, B21 ... Strike Pitch processing unit.

Claims (8)

In a radar apparatus that transmits and receives N (N> 1) pulses in an arbitrary direction and detects a target from the received signal,
Conversion means for converting the received signal of the pulse into a frequency domain with respect to a PRI (Pulse Repetition Interval) axis;
An acquisition means for acquiring FR data (Doppler range data) for P (P ≧ 2) times by shifting the time from the received signal in the frequency domain converted by the conversion means;
Creating means for creating an optical flow diagram and an amplitude intensity diagram from the FR data for the P times;
Calculation means for calculating a feature quantity based on a velocity vector and amplitude intensity based on the optical flow diagram and amplitude intensity diagram created by the creation means;
A radar apparatus comprising: detecting means for detecting as a target when the feature amount exceeds a predetermined threshold. The calculation means calculates the absolute value of the addition value of the amplitude intensity and the addition value of the velocity vector around the extreme value of the amplitude intensity diagram as the feature amount,
The radar apparatus according to claim 1, wherein the detection unit detects a target when an absolute value of an addition value of an amplitude intensity and an addition value of a velocity vector of the predetermined cell range exceeds a predetermined threshold.   The acquisition means converts the FR data acquired from the signal in the frequency domain into a frequency domain with a two-dimensional FFT (Fast Fourier Transform), fills a two-dimensional axis with zeros, and then converts it into the time domain with a two-dimensional inverse FFT. The radar apparatus according to claim 1 or 2. The acquisition means converts the FR data acquired from the frequency domain signal or the FR data into a frequency domain using a two-dimensional FFT (Fast Fourier Transform), fills a two-dimensional axis with zeros, and then converts the two-dimensional inverse Obtain the FR data converted to the time domain by FFT,
The detection unit extracts an amplitude extreme value exceeding a predetermined threshold from the FR data acquired by the acquisition unit or the FR data after zero padding, and a predetermined coefficient is added to the extreme amplitude value in a cell around the extreme value. The radar apparatus according to claim 1, wherein the target is detected after stretching by replacing with an amplitude value multiplied by. In a radar signal processing method of a radar apparatus that transmits and receives N (N> 1) pulses in an arbitrary direction and detects a target from the received signal,
The received signal of the pulse is converted into a frequency domain with respect to a PRI (Pulse Repetition Interval) axis,
Obtain FR data (Doppler range data) from the received signal converted into the frequency domain by shifting the time by P (P ≧ 2) times,
Create an optical flow diagram and amplitude intensity diagram from the FR data for P times,
Based on the optical flow diagram and the amplitude intensity diagram, the feature quantity by the velocity vector and the amplitude intensity is calculated,
A radar signal processing method of a radar apparatus that detects a target when the feature amount exceeds a predetermined threshold. Centering on the extreme value of the amplitude intensity diagram, the absolute value of the added value of the amplitude intensity of the predetermined cell range and the added value of the velocity vector is calculated as the feature amount,
6. The radar signal processing method of a radar apparatus according to claim 5, wherein a detection is made as a target when the absolute value of the sum of the amplitude intensity and the sum of the velocity vector in the predetermined cell range exceeds a predetermined threshold.   The FR data acquired from the signal in the frequency domain is converted to the frequency domain by a two-dimensional FFT (Fast Fourier Transform), zero-padded on a two-dimensional axis, and then converted to the time domain by a two-dimensional inverse FFT. 7. A radar signal processing method for a radar device according to 5 or 6. The FR data acquired from the signal in the frequency domain, or the FR data is converted into the frequency domain by two-dimensional FFT (Fast Fourier Transform), zero-padded in the two-dimensional axis, and then converted into the time domain by two-dimensional inverse FFT Obtain the converted FR data,
Amplitude extreme values exceeding a predetermined threshold are extracted from the FR data acquired from the signal in the frequency domain or the FR data after zero padding, and an amplitude obtained by multiplying a cell around the extreme value by a predetermined coefficient to the amplitude value of the extreme value The radar signal processing method of a radar apparatus according to claim 5, wherein the target is detected after being replaced with a value and stretched.

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