CN106842146B - Engineering implementation method for phase coding signal sidelobe suppression - Google Patents
Engineering implementation method for phase coding signal sidelobe suppression Download PDFInfo
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Abstract
The invention provides an engineering realization method for phase coding signal sidelobe suppression, which is characterized by comprising the following steps of: step by stepStep 1, sampling original echo data to form a discrete echo input vector S (n), wherein the length of S (n) is L, and the sampling length corresponding to the pulse width of a radar emission signal is M; step 2, determining the times of the segmented pulse pressure according to the capacity of a processing chip, wherein P times of processing is assumed; every time the number of pulse pressure processing points is N, extracting the point data from 1 to N of S (N) to obtain a new data vector X1(n); step 3, performing N-point discrete Fourier transform on S (N) to obtain S (w), performing N-point discrete Fourier transform on the side lobe suppression filter with the length of K M and the K being multiple to obtain H (w), performing point-to-point multiplication on S (w) and H (w), and performing N-point inverse discrete Fourier transform to obtain a vector Y1(n)。
Description
Technical Field
the invention belongs to the field of airborne radars, and relates to realization of a pulse compression algorithm of a phase coding signal in radar signal processing.
Background
the phase coding signal has good anti-interference performance, high time delay and Doppler resolution capability and no range-Doppler coupling, so the phase coding signal is widely applied to radar waveform design, but the phase coding signal generates higher range sidelobe due to non-ideal correlation characteristics among phase coding codewords and the influence of Doppler frequency in echo, and the detection of a small target signal is greatly influenced. Therefore, sidelobe suppression is required for the phase-encoded signal. The sidelobe suppression filter is a mismatch filter essentially, and the length of the filter coefficient is inconsistent with the length of the coded signal, so that the matched filtering algorithm widely used by the original linear frequency modulation signal cannot be applied.
Algorithms for designing phase coding signal sidelobe suppression filters are published in Wanfang and Weipu databases, but the algorithms do not have an article how to realize the radar. Pulse compression in radar engineering is realized by a frequency fast convolution method. The process of the frequency domain fast convolution method is as follows: the method comprises the steps of firstly carrying out FFT processing on a baseband sampling echo signal epsilon (n) to obtain a corresponding frequency spectrum epsilon (w), then multiplying epsilon (w) with a filtering frequency response H (w), and finally carrying out IFFT operation on a multiplied result to obtain a time domain pulse compression result.
when the original sampling data is long, the data needs to be processed in a segmented mode in the pulse compression process. Because the length of the sidelobe suppression filter is not consistent with that of the matched filter, the matched filtering algorithm is directly applied to perform pulse compression on the phase coding signal in radar signal processing, abnormal sidelobes can be generated at the initial position and the segmentation position of the compressed signal, and therefore a project suitable for the sidelobe suppression mismatched filter needs to be designed to realize the pulse pressure algorithm.
disclosure of Invention
By designing a pulse compression implementation algorithm of the sidelobe suppression filter, the purpose of suppressing abnormal sidelobes caused by applying a matched filtering algorithm during segmented pulse pressure is achieved.
Technical scheme
The invention provides an engineering realization method for sidelobe suppression of a phase coding signal, which is characterized by comprising the following steps of:
step 1
Sampling original echo data to form a discrete echo input vector S (n), wherein the length of S (n) is L, and the sampling length corresponding to the pulse width of a radar emission signal is M;
Step 2
Determining the times of segmented pulse pressure according to the capacity of a processing chip, wherein P times of processing are assumed, and the number of processing points of each pulse pressure is N;
Step 3
Extracting the point data from 1 to N in the step(s) to obtain a new data vector X1 (N); performing N-point discrete Fourier transform on S (N) to obtain S (w), performing N-point discrete Fourier transform on the sidelobe suppression filter with the length K M and the K being multiple to obtain H (w), performing point-to-point multiplication on S (w) and H (w), and performing N-point inverse discrete Fourier transform to obtain a vector Y1 (N);
Step 4
Defining discrete echo output vector as O (N), filling 0 from 1 to (K-1) M/2 of O (N), (K-1) M/2+1 to N- (K +1) M/2 to take the value at the same position of Y1 (N);
Step 5
processing 2, taking the starting position: N-K M +1, overlapping K M points with the data processed for the 1 st time, and setting the counting length N point, namely the counting end point as 2N-K M; obtaining a new data vector X2(N), repeating the step 3 to obtain a vector Y2(N), and filling the data from (K-1) × M/2+1 to N- (K +1) × M/2 of Y2(N) into the positions of N- (K +1) × M/2+1 to 2 × N- (3K +1) × M/2 of O (N);
Step 6
Processing from the 3 rd time to the P-1 st time in the same step 5 to obtain Y3(n) … Yp-1(n), and filling data of corresponding positions into O (n);
step 7
in the P-th processing, if the length of the collected data is still N, the P-segment processing is consistent with the previous P-1-segment processing, the step 5 is repeated to obtain Yp (N), and the data from (K-1) M/2+1 to N- (K +1) M/2 of Yp (N) is connected to the tail part of O (N);
If the length of the collected data is smaller than N, setting the length as R, carrying out zero filling processing on the following N-R data, then carrying out discrete Fourier transformation, repeating the step 5, and connecting (K-1) M/2+1 to R- (K +1) M/2 of Yp (N) to the tail part of O (N);
wherein (K-1) M/2, (K-1) M/2+1, N- (K +1) M/2+1, 2N- (3K +1) M/2 and R- (K +1) M/2 are positive integers between 1 and N.
In modern war, the radar is required to have not only higher detection capability, but also low interception probability performance and strong electronic anti-rejection capability. The phase coding signal radar has good anti-interference performance and low interception probability, and has great requirements in military application, but the use of the phase coding signal radar is limited due to high range sidelobe, so that the engineering realization of adopting a proper algorithm to suppress the sidelobe of the phase coding signal is the key for exerting the performance of the phase coding signal and applying the phase coding signal in the radar, and the key for improving the detection probability of the small target signal in a multi-target environment.
Drawings
Fig. 1 is a block diagram of a frequency domain fast convolution implementation, in which AD represents the conversion of an analog quantity to a digital quantity, FFT represents the discrete fourier transform, and IFFT represents the inverse discrete fourier transform.
Fig. 2 is a schematic diagram of an overlap-and-hold method used in matched filtering segmented pulse pressure, where L is a data sample length, M is a matched filter length, and N is a data length of each pulse pressure.
Fig. 3 is a diagram of abnormal side lobes when mismatched filtering is performed for side lobe suppression by using an overlap-save method for matched filtering segmented pulse pressure, in the diagram, the length of a side lobe suppression filter is 1500, the sampling length corresponding to the pulse width is 750, the processing is divided into two sections, 8192-point pulse compression is performed each time, and after a matched filtering algorithm is applied, abnormal side lobes appear at the front edge and the middle segmented position of an output signal.
Figure 4 is a schematic diagram of the number of valid data points of mismatched pulse pressure of a sidelobe suppression filter,
Fig. 5 is a graph of the effect of pulse compression following the steps of sidelobe suppression shown herein, with no abnormal sidelobes present, as compared to fig. 3.
Detailed Description
Step 1
sampling original echo data to form a discrete echo vector S (n), wherein the length of S (n) is L, and the sampling length corresponding to the pulse width of a radar emission signal is M;
Step 2
determining the times of segmented pulse pressure according to the capacity of a processing chip, wherein P times of processing are assumed, and the number of processing points of each pulse pressure is N;
Step 3
Extracting the data from 1 to N points of S (N) to obtain a new data vector X1(n); performing N-point discrete Fourier transform on S (N) to obtain S (w), performing N-point discrete Fourier transform on the sidelobe suppression filter with the length K M and the K multiple to obtain H (w), performing point-to-point multiplication on S (w) and H (w), and performing N-point inverse discrete Fourier transform to obtain a vector Y1(n)；
Step 4
Defining output vector as O (N), filling 0 from 1 to (K-1) M/2 of O (N), (K-1) M/2+1 to N- (K +1) M/2 to take Y1(n) the value at the same position. Referring to fig. 4, the pulse width of the signal corresponds to the number of sampling points: m, the width of the sidelobe suppression filter is set to K M, K is a multiple, the number of FFT points is N every time when pulse pressure is carried out, and signals are compressed to the front edge through shifting when the pulse pressure is carried out. For a complete signal of data start, such as signal 1 in the figure, the distance from the start point is R, the length of a side flap folded to the tail after pulse pressure is (K +1) M/2-R, R is more than 0, and the length of the side flap is at most (K +1) M/2; for an incomplete signal of the beginning of the data, such as signal 2 in the figure, the length of the signal is R,The length of the data after pulse pressure is K M + R, and after the pulse pressure is shifted, the data has (K-1) M/2+ R points from the beginning of the data, and the convolution shows that only the R point data is valid after the data with the length of the second half R is convoluted, so the (K-1) M/2 point data at the beginning of the data is invalid; for the complete signal of the tail, as signal 3 in the figure, the distance R from the end point N of the fetch length is greater than or equal to M, and the signal range after pulse pressure is: N-R- (K +1) M/2-N-R + (K +1) M/2, the length of the side valve folded to the beginning of data after pulse pressure is (K +1) M/2-R, and the length of (K +1) M/2-R is less than or equal to (K-1) M/2 obtained by R being more than or equal to M; for the incomplete signal at the tail, such as signal 4 in the figure, the distance R of the leading edge of the signal from the end point N of the counting length<m, the signal range after pulse pressure is: N-R- (K +1) M/2-N + (K +1) M/2, and the length of the secondary valve folded to the beginning of the data is (K-1) M/2; the effective signals are N-R- (K +1) M/2-N- (K +1) M/2. It can be seen from the above that, 1 to N points of data are taken when taking the number, after compression, (K-1) M/2 at the beginning should be discarded, and (K +1) M/2 at the end should be discarded;
Step 5
processing 2, taking the starting position: N-K M +1 (overlapping K M points), and setting the counting length N point, namely the counting end point as 2N-K M; obtaining a new data vector X2(N), repeating the step 3 to obtain a vector Y2(N), and filling the data from (K-1) × M/2+1 to N- (K +1) × M/2 of Y2(N) into the positions of N- (K +1) × M/2+1 to 2 × N- (3K +1) × M/2 of O (N);
step 6
Processing from the 3 rd time to the P-1 st time in the same step 5 to obtain Y3(n) … Yp-1(n), and filling data of corresponding positions into O (n); (ii) a
step 7
In the P-th processing, if the length of the collected data is still N, the P-segment processing is consistent with the previous P-1-segment processing, the step 5 is repeated to obtain Yp (N), and the data from (K-1) M/2+1 to N- (K +1) M/2 of Yp (N) is connected to the tail part of O (N);
If the length of the collected data is smaller than N, setting the length as R, carrying out zero filling processing on the following N-R data, then carrying out discrete Fourier transformation, repeating the step 5, and connecting (K-1) M/2+1 to R- (K +1) M/2 of Yp (N) to the tail part of O (N);
Wherein (K-1) M/2, (K-1) M/2+1, N- (K +1) M/2+1, 2N- (3K +1) M/2 and R- (K +1) M/2 are positive integers between 1 and N.
Claims (1)
1. The engineering realization method for suppressing the sidelobe of the phase coding signal is characterized by comprising the following steps of:
Step 1
Sampling original echo data to form a discrete echo input vector S (n), wherein the length of S (n) is L, and the sampling length corresponding to the pulse width of a radar emission signal is M;
step 2
Determining the times of segmented pulse pressure according to the capacity of a processing chip, wherein P times of processing are assumed, and the number of processing points of each pulse pressure is N;
Step 3
Extracting the data from 1 to N points of S (N) to obtain a new data vector X1(n); performing N-point discrete Fourier transform on S (N) to obtain S (w), performing N-point discrete Fourier transform on the sidelobe suppression filter with the length K M and the K multiple to obtain H (w), performing point-to-point multiplication on S (w) and H (w), and performing N-point inverse discrete Fourier transform to obtain a vector Y1(n)；
step 4
Defining discrete echo output vector as O (N), filling 0 from 1 to (K-1) M/2 of O (N), (K-1) M/2+1 to N- (K +1) M/2 to take Y1(n) a value at the same position; the 1 st treatment comprises a step 3 and a step 4;
step 5
processing 2, taking the starting position: N-K M +1, overlapping K M points with the data processed for the 1 st time, and setting the counting length N point, namely the counting end point as 2N-K M; obtaining a new data vector X2(N), repeating the step 3 to obtain a vector Y2(N), and filling the data from (K-1) × M/2+1 to N- (K +1) × M/2 of Y2(N) into the positions of N- (K +1) × M/2+1 to 2 × N- (3K +1) × M/2 of O (N);
Step 6
treating from 3 rd to P-1 th in the same step as step 5 to obtain Y3(n)…Yp-1(n), and filling data of the corresponding position into O (n);
Step 7
in the P-th processing, if the length of the collected data is still N, the P-segment processing is consistent with the previous P-1-segment processing, the step 5 is repeated to obtain Yp (N), and the data from (K-1) M/2+1 to N- (K +1) M/2 of Yp (N) is connected to the tail part of O (N); if the length of the collected data is smaller than N, setting the length as R, carrying out zero filling processing on the following N-R data, then carrying out discrete Fourier transformation, repeating the step 5, and connecting (K-1) M/2+1 to R- (K +1) M/2 of Yp (N) to the tail part of O (N);
Wherein (K-1) M/2, (K-1) M/2+1, N- (K +1) M/2+1, 2N- (3K +1) M/2 and R- (K +1) M/2 are positive integers between 1 and N.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05107339A (en) * | 1991-10-15 | 1993-04-27 | Nec Corp | Signal processing method for radar |
| CN103064063A (en) * | 2011-10-21 | 2013-04-24 | 中国人民解放军海军航空工程学院 | Poly-phase code radar signal waveform automatic identification method based on continuous wave Doppler (CWD) feature |
| CN103116669A (en) * | 2013-01-25 | 2013-05-22 | 西安电子科技大学 | Design method for ultralow sidelobe pseudorandom noise signals |
| CN103499812A (en) * | 2013-09-23 | 2014-01-08 | 中国科学院电子学研究所 | Baseband signal predistortion method of broadband multi-channel coherent radar imaging system |
| CN106342323B (en) * | 2011-12-27 | 2014-06-18 | 中国航空工业集团公司雷华电子技术研究所 | The submatrix weighted value of phased-array radar difference beam Sidelobe Suppression is determined method |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05107339A (en) * | 1991-10-15 | 1993-04-27 | Nec Corp | Signal processing method for radar |
| CN103064063A (en) * | 2011-10-21 | 2013-04-24 | 中国人民解放军海军航空工程学院 | Poly-phase code radar signal waveform automatic identification method based on continuous wave Doppler (CWD) feature |
| CN106342323B (en) * | 2011-12-27 | 2014-06-18 | 中国航空工业集团公司雷华电子技术研究所 | The submatrix weighted value of phased-array radar difference beam Sidelobe Suppression is determined method |
| CN103116669A (en) * | 2013-01-25 | 2013-05-22 | 西安电子科技大学 | Design method for ultralow sidelobe pseudorandom noise signals |
| CN103499812A (en) * | 2013-09-23 | 2014-01-08 | 中国科学院电子学研究所 | Baseband signal predistortion method of broadband multi-channel coherent radar imaging system |
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