A sidelobe cancellation method for adaptive multipath interference suppression in clutter environments

Abstract

The present invention relates to the field of radar anti-interference, and in particular to a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment. The present invention removes the clutter component in the signal by performing pulse-to-pulse FFT on the echo signal and utilizing the low-frequency characteristics of ground clutter to remove the low-frequency part in the frequency domain, thereby solving the problem of decreased sidelobe cancellation performance in a clutter environment in the traditional method; the correlation function of the echo signal of the main antenna and the auxiliary antenna is obtained, and the number of adaptive delay nodes is obtained according to the correlation result, so as to realize adaptive multipath interference suppression, thereby solving the problems of complex calculation and large amount of calculation caused by not knowing the number of delay nodes.

Description

Technical Field

[0001] The invention relates to the field of radar anti-active interference, and in particular to a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment. Background Art

[0002] Active interference resistance is still a challenge that radars need to deal with in modern warfare. With the continuous improvement of array antennas and high-speed signal processing technology, there are also many types of adaptive array processing technology to combat active interference. Adaptive sidelobe cancellation technology is an essential measure for modern radars to resist active interference. Its basic principle is to place several auxiliary antennas next to the main antenna, or to extract a subarray of the main antenna as an auxiliary antenna, and automatically adjust the auxiliary antenna weight according to different input information. The weight correction of the auxiliary antenna mainly changes the directional pattern of the auxiliary antenna, so that the directional pattern of the main antenna and the directional pattern of the auxiliary antenna form a zero point in the interference direction after spatial synthesis, thereby realizing the weighting of the interference signal received by the auxiliary antenna to cancel the interference signal received in the main antenna.

[0003] However, in the specific development process of radar, due to factors such as topography and weather, the interference source multipath propagation, strong clutter and other problems have limited the effectiveness of the various methods mentioned in the patent literature in practical applications. Conventional elimination of multipath interference is to increase the degree of freedom of adaptive processing by adding delay nodes in the auxiliary channel, thereby improving the ability to suppress multipath interference. Since it is not known in advance how large the delay of multipath interference is relative to direct interference, many delay nodes need to be added in actual engineering implementation, and the complexity and amount of calculation are significantly increased. This is a significant disadvantage of conventional methods. In a strong clutter environment, the conventional method is to first perform two-pulse or three-pulse cancellation, and then perform sidelobe cancellation, which will result in excessive target loss, especially for low-speed targets.

[0004] Therefore, a method is needed to solve the problem of complex and large amount of calculation of multipath interference in clutter environment. Summary of the invention

[0005] In view of the shortcomings of the traditional sidelobe cancellation method in the background technology when multipath interference and clutter exist at the same time, such as complex calculation, large amount of calculation, loss of low-speed targets, and difficulty in engineering implementation, the present invention proposes a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment. The method of the present invention includes a method for removing clutter from an echo signal and a method for implementing adaptive multipath suppression. The present invention has the advantages of versatility, high calculation efficiency, and easy implementation in engineering, and has been applied to a certain radar and successfully verified.

[0006] In order to solve the above technical problems, the technical solution of the present invention is a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment, comprising:

[0007] Step 1: Perform intra-wave accumulation of the main antenna echo signal;

[0008] Step 2: Perform intra-wavelength accumulation of the auxiliary antenna echo signal

[0009] Step 3: Perform pulse-to-pulse FFT on the accumulated echo signal;

[0010] Step 4: Remove the 0-frequency and ±1-frequency components from the pulse-to-pulse FFT result, and then perform IFFT to obtain the new main antenna echo signal and auxiliary antenna echo signal;

[0011] The beneficial effect of step 1 to step 4 is: without considering the target signal, in a clutter environment, the echo signal contains two parts, wherein the first part represents the received signal in which clutter and noise coexist, and the second part represents the received signal in which interference signal, clutter and noise coexist. By utilizing the 0-frequency characteristic of ground clutter, the clutter component in the signal can be removed by removing the 0-frequency and ±1-frequency parts in the frequency domain. At this time, the new signal on the main antenna and the auxiliary antenna no longer contains clutter, and only the interference signal and noise remain. Selecting samples from the new signal and calculating the adaptive weights can greatly improve the cancellation capability of the system.

[0012] Step 5: Calculate the number of adaptive delay sections for the new main antenna echo signal and auxiliary antenna echo signal segment by segment:

[0013] Step 5a: Segment the echo data;

[0014] Step 5b: Calculate the correlation function for the segmented echo data respectively, and select the positions corresponding to the largest 7 peaks according to the correlation results, corresponding to 7 delay sections;

[0015] Step 5c: construct an expansion matrix according to the delay nodes obtained in step 5b;

[0016] Step 5d: Obtain the optimal weight according to the minimum mean square error criterion;

[0017] Step 5e: repeat steps 5b to 5d to obtain the optimal weights of the segmented cancellation of all pulse repetition period echo signals of the main antenna echo signal matrix and the auxiliary antenna echo signal matrix;

[0018] The beneficial effect of this step is: due to the rotation of the antenna and the interference frequency sweep, the pulse is processed in segments, that is, a single pulse is evenly divided into several segments, and the adaptive weight of each segment is calculated separately. The weight calculated for each segment is only used to cancel the original received data of this segment. The beneficial effect of obtaining the correlation function of the echo signal of the main antenna and the auxiliary antenna is: the correlation result of the echo signal of the main and auxiliary antennas is composed of a series of peaks, and the correlation result is modulo, and the position corresponding to the largest 7 peaks is selected, which is the number of distance units of the delay section. The 7 different delay sections here are obtained by processing real data and combining computing power. According to the relevant results, the number of adaptive delay sections is obtained, and adaptive multipath interference suppression is realized, which solves the problems of complex calculation and large amount of calculation caused by not knowing the number of delay sections.

[0019] Step 6: Segment each pulse repetition period in the original main antenna echo signal matrix and the auxiliary antenna echo signal matrix;

[0020] Step 7: construct an auxiliary channel echo signal matrix extension matrix according to the delay node vector obtained in step 5b;

[0021] Step 8: Segmentally calculate the echo signal of each pulse repetition period in the main antenna echo signal matrix and the auxiliary antenna echo signal matrix to obtain the main antenna echo matrix after cancellation.

[0022] The beneficial effects of the present invention are as follows: accumulating echo signals within a wave position, performing FFT, utilizing the characteristic of the zero frequency of ground clutter, removing the zero frequency and ±1 frequency parts in the frequency domain, thereby removing the clutter components in the signal, and then performing IFFT. At this time, the new signals on the main antenna and the auxiliary antenna no longer contain clutter, and only the interference signal and noise are left, thereby solving the problem of the degradation of the sidelobe cancellation performance in the clutter environment of the traditional method; segmenting the pulse due to the rotation of the antenna and the interference frequency sweep, that is, evenly dividing a single pulse into several segments, calculating the adaptive weight of each segment respectively, and the weight calculated for each segment is only used to cancel the original received data of the segment; obtaining the correlation function of the echo signals of the main antenna and the auxiliary antenna, obtaining the number of adaptive delay nodes according to the result of the correlation function, realizing adaptive multipath interference suppression, and solving the problems of complex calculation and large amount of calculation caused by not knowing the number of delay nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The invention is a flow chart of steps 1 to 4 in a specific embodiment of a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment;

[0024] Figure 2 It is a flow chart of steps 5 to 8 in a specific embodiment of a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment;

[0025] Figure 3 It is to collect radar echo signals with multipath interference and clutter;

[0026] Figure 4 The invention compares the processing results of radar collected data by the traditional method and the method of the invention.

[0027] Explanation of the names: FFT: Fourier transform; IFFT: Inverse Fourier transform; xcorr: Calculate the correlation function. DETAILED DESCRIPTION

[0028] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0029] The embodiment of the present invention provides a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment, which can be applied to the field of radar anti-active interference.

[0030] See also Figure 1 and Figure 2 , a sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment comprises the following steps:

[0031] Step 1: The main antenna receives a period of echo signal using the vector X1 = [x1, x2, ..., x M ] means, where x1,x2,…,x M is the echo value of M range units;

[0032] Step 2: The auxiliary antenna receives a periodic echo signal using the vector Y1 = [y1, y2, ..., y M ] means, where y1,y2,…,y M is the echo value of M range units;

[0033] Step 3: Repeat steps 1 and 2 to accumulate multiple pulse repetition periods in the wave position and obtain the main channel echo signal matrix A = [X1, X2, ..., X N ] T , auxiliary channel echo signal matrix B = [Y1, Y2, ..., Y N ] T , respectively perform pulse-to-pulse FFT on the received signals on the main channel and the auxiliary channel, that is, perform N-point FFT on the signals received within N pulse repetition periods. The purpose of this step is to utilize the low-frequency characteristics of clutter, and remove the clutter components in the signal by removing the 0-frequency and ±1-frequency parts in the frequency domain;

[0034] Step 4: Set the 0-frequency and ±1-frequency channel outputs of the main antenna and auxiliary antenna after FFT processing to 0, and then perform IFFT to obtain the new main antenna echo signal matrix A′=[X′1,X′2,…,X′ N ] Tand auxiliary antenna signal matrix B′=[Y′1,Y′2,…,Y′ N ] T At this time, the main antenna echo signal and the auxiliary antenna signal no longer contain clutter, and only interference signals and noise remain. Selecting samples from the new signal and calculating adaptive weights can greatly improve the system's cancellation capability;

[0035] Step 5: Based on the new main antenna echo matrix A′=[X′1,X′2,…,X′ N ] T and the auxiliary antenna echo matrix B′=[Y′1,Y′2,…,Y′ N ] T For N pulses, calculate the number of delay nodes respectively:

[0036] Step 5a: For X′ i and Y′ i The values ​​of the M distance units are segmented into K segments of equal length to obtain X′ ik and Y ik ′, whose length is M / K, i=1,2,3,...,N. The purpose of segmentation in this step is: considering the reasons of antenna rotation and interference frequency sweep, the pulse is segmented, that is, a single pulse is evenly divided into several segments, and the adaptive weight of each segment is calculated respectively, so as to reduce the modulation influence of antenna rotation and interference frequency sweep on the received wave;

[0037] Step 5b: For X′ ik and Y ik ′Find the correlation function φ ik ,φ ik = xcorr(X′ ik ,Y′ ik ), the purpose of this step is to obtain the correlation between the main antenna and the auxiliary antenna signal, to modulo the correlation result, to select the position corresponding to the largest 7 peaks to obtain the number of adaptive delay nodes, that is, the number of distance units of the delay node, that is, the delay node vector T ik =[τ ik1 , τ ik2 , τ ik3 ,...,τ ik7 ], 7 different delay nodes are selected here by processing real data and combining computing power. If 6 delay nodes are selected, the cancellation effect is poor. If 8 delay nodes are selected, the cancellation effect is not much improved, but the amount of calculation is relatively large. Considering comprehensively, 7 delay nodes are selected;

[0038] Step 5c: Delay node vector T obtained in step 5b ik , construct the expansion matrix and Calculate the autocorrelation matrix R of the auxiliary antenna echo respectively ik =Y″ik H Y″ ik And the main antenna and auxiliary antenna echo autocorrelation matrix P ik =Y″ ik X″ ik H ;

[0039] Step 5d: According to the minimum mean square error criterion, the adaptive sidelobe cancellation coefficient W is obtained ik =R ik -1 P ik ;

[0040] Step 5e: Repeat steps 5b to 5d to obtain the main antenna echo signal matrix A′=[X′1,X′2,…,X′ N ] T and the auxiliary antenna echo signal matrix B′=[Y′1,Y′2,…,Y′ N ] T The optimal weight W for the segmented cancellation of all pulse repetition period echo signals ik ;

[0041] Step 5 combines the existing adaptive sidelobe cancellation technology and takes into account the reasons of antenna rotation and interference frequency sweeping to process the pulse in segments, that is, to evenly divide a single pulse into several segments, and calculate the adaptive weight of each segment respectively, so as to reduce the modulation influence of antenna rotation and interference frequency sweeping on the received wave; the delay of multipath interference relative to direct interference is obtained by calculating the correlation function of the interference signal in the main and auxiliary antennas, and then the direct interference signal of the auxiliary antenna is delayed by the delay node to obtain a virtual auxiliary antenna interference input, and finally the weight of the auxiliary antenna is obtained according to the minimum mean square error criterion, so that the output power of the main and auxiliary antenna cancellation after weighted processing is minimized; direct interference and multipath interference are considered while calculating the weight vector, so that the interference cancellation performance is better, and the method of calculating the delay node by the correlation function is adaptive.

[0042] Step 6: For the main antenna echo signal matrix A = [X1, X2, ..., X N ] T and auxiliary antenna echo signal matrix B = [Y1, Y2, ..., Y N ] T Each pulse repetition period X i and Y i The values ​​of the M distance units are segmented into K segments of equal length to obtain X ik and Y ik , whose length is M / K, i=1,2,3,...,N;

[0043] Step 7: Delay node vector T obtained from step 5b ik, construct the auxiliary antenna echo signal matrix expansion matrix

[0044] Step 8: Calculate the result after sidelobe cancellation, X″′ ik =X ik -W ik T Y″′ ik , and then the main antenna echo signal matrix A=[X1,X2,…,X N ] T and auxiliary antenna echo signal matrix B = [Y1, Y2, ..., Y N ] T The echo signal of each pulse repetition period within the range is calculated segmentally to obtain the main antenna echo matrix A″=[X″′1,X″′2,…,X″′ N ] T .

[0045] Figure 3 It is a radar that collects radar echo signals with multipath interference and clutter. Figure 4 The invention compares the processing results of radar collected data by the traditional method and the method of the invention. Figure 3 and Figure 4 In the figure, the horizontal axis is the distance unit and the vertical axis is the interference amplitude. It can be seen from the figure that under the same conditions, the interference cancellation result using the method of the present invention is better than that of the traditional processing method. The cancellation residual of the method of the present invention is improved by 10dB at most compared with the traditional method.

[0046] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment, characterized by: The following steps are involved: Step 1: Perform intra-wave accumulation of the main antenna echo signal; Step 2: Perform intra-wavelength accumulation of the auxiliary antenna echo signal; Step 3: Perform pulse-to-pulse FFT on the accumulated echo signal; Step 4: Remove the 0-frequency and ±1-frequency components from the pulse-to-pulse FFT result, and then perform IFFT to obtain the new main antenna echo signal and auxiliary antenna echo signal; Step 5: Calculate the number of adaptive delay sections for the new main antenna echo signal and auxiliary antenna echo signal segment by segment: Step 5a: Segment the echo data; Step 5b: Calculate the correlation function for the segmented echo data respectively, and select the positions corresponding to the largest 7 peaks according to the correlation results, corresponding to 7 delay sections; Step 5c: construct an expansion matrix according to the delay nodes obtained in step 5b; Step 5d: Obtain the optimal weight according to the minimum mean square error criterion; Step 5e: repeat steps 5b to 5d to obtain the optimal weights of the segmented cancellation of all pulse repetition period echo signals of the main antenna echo signal matrix and the auxiliary antenna echo signal matrix; Step 6: segmenting each pulse repetition period in the original main channel echo signal matrix and the auxiliary channel echo signal matrix; Step 7: construct an auxiliary channel echo signal matrix extension matrix according to the delay node vector obtained in step 5b; Step 8: Segmentally calculate the echo signals of each pulse repetition period in the main channel echo signal matrix and the auxiliary channel echo signal matrix to obtain the canceled main channel echo matrix.

2. The sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment according to claim 1, characterized in that: In step 3, an N-point pulse-to-pulse FFT is performed on the received signals on the main channel and the auxiliary channel.

3. The sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment according to claim 1, characterized in that: The correlation function φ in step 5b ik ,φ ik = xcorr(X i ' k ,Y ik ′), X i ' k The distance unit value of the main antenna echo signal is segmented into K segments of equal length; Y ik ' is the value of the distance unit of the auxiliary antenna signal, which is divided into K segments of equal length.

4. The sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment according to claim 3, characterized in that: The expanded matrix in step 5c is and 5. The sidelobe cancellation method for adaptive multipath interference suppression in a clutter environment according to claim 1, characterized in that: The optimal weight W in step 5d ik =R ik -1 P ik ;P ik is the auxiliary antenna echo autocorrelation matrix; R ik is the autocorrelation matrix of the auxiliary antenna echo, R ik -1 is its inverse matrix.

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