阅读说明：本技术 一种雷达自适应旁瓣相消算法 (Radar self-adaptive sidelobe cancellation algorithm ) 是由 田红 于 2020-12-25 设计创作，主要内容包括：本发明公开了一种雷达自适应旁瓣相消算法,自适应旁瓣相消系统,包括一个主通道与若干个辅助通道。主通道信号由主天线加权后合成,用于确定目标指向,具有方向性强、波束宽度窄、副瓣电平低等特点。辅助通道信号由各辅助天线单独送入,辅助天线通常为低增益的全向天线,其增益与主天线的副瓣电平相当。当期望信号与干扰同时到达主辅天线时,辅助通道中期望信号分量远小于主通道中期望信号分量,而干扰幅度却大致相当。如果对辅助通道进行实时加权求和以弥补主辅通道间由波程差引起的固定相位差,再同主通道输出做相减运算,即可自适应的对消干扰。(The invention discloses a radar self-adaptive side lobe cancellation algorithm, and a self-adaptive side lobe cancellation system. The main channel signals are weighted by the main antenna and then synthesized for determining the target direction, and the method has the characteristics of strong directivity, narrow beam width, low side lobe level and the like. The auxiliary channel signals are fed separately from each auxiliary antenna, which is typically a low gain omni-directional antenna with a gain comparable to the main antenna side lobe level. When the desired signal arrives at the main and auxiliary antennas simultaneously with the interference, the desired signal component in the auxiliary channel is much smaller than the desired signal component in the main channel, while the interference magnitude is roughly comparable. If the auxiliary channels are weighted and summed in real time to make up for the fixed phase difference caused by the wave path difference between the main channel and the auxiliary channel, and then the subtraction operation is carried out with the output of the main channel, the self-adaptive interference cancellation can be realized.)

1. A radar adaptive sidelobe canceling algorithm is characterized in that: comprises a main channel and a plurality of auxiliary channels; the main channel signals are weighted by the main antenna and then synthesized, and are used for determining the target direction; the auxiliary channel signals are fed separately from each auxiliary antenna, which is typically a low gain omni-directional antenna with a gain comparable to the main antenna side lobe level. When the desired signal and the interference reach the main antenna and the auxiliary antenna simultaneously, the desired signal component in the auxiliary channel is far smaller than the desired signal component in the main channel; if the auxiliary channels are weighted and summed in real time to make up for the fixed phase difference caused by the wave path difference between the main channel and the auxiliary channel, and then the subtraction operation is carried out with the output of the main channel, the self-adaptive interference cancellation can be realized.

2. The radar adaptive sidelobe canceling algorithm of claim 1, wherein: adaptive sidelobe canceling using V₀Representing the destructive output, can be expressed as:wherein X represents a signal received by the main antenna; y ═ Y₁，Y₂，...，Y_N]^TRepresenting signals received by the auxiliary antenna; w ═ W₁，W₂，...，W_N]^TRepresents a weighting coefficient; "+" indicatesConjugation, "H" denotes conjugation transpose, and "T" denotes transpose.

3. A radar adaptive sidelobe canceling algorithm according to claim 2, wherein: in order to minimize the total power output, the least mean square criterion is usually adopted, whose mean square value is ξ ═ E [ | V |)₀|²]The optimal weight vector that is expanded and derived to minimize ξ is:R_XYmatrix of cross-correlation functions, R, representing main and auxiliary channels_YYA matrix of autocorrelation functions representing the secondary channels.

4. The radar adaptive sidelobe canceling algorithm of claim 1, wherein: the method comprises the following steps:

A. effectively selecting SLC interference sample points;

B. and (5) real-time calculation of the multi-dimensional matrix.

5. The radar adaptive sidelobe canceling algorithm of claim 4, wherein: the adaptive interference sampling method in the step A is as follows:

a. dividing echo data of a main antenna and an auxiliary antenna in a detection distance into N sections, wherein the sampling length of each section is 32, 64, 128, 256 and the like;

b. after the main and auxiliary channel data are sampled in a segmented mode, weight coefficients of each segmented data are calculated sequentially, cancellation results of each data are obtained respectively, and the cancellation result data of each data are spliced to obtain a final cancellation processing result.

6. The radar adaptive sidelobe canceling algorithm of claim 4, wherein: aiming at the problems that the number of sampling points is too large or the matrix scale is too large, and a large amount of time is consumed when the cancellation weight coefficient is calculated, parallel optimization functions are adopted in software implementation to optimize matrix operation.

Technical Field

The invention relates to the technical field of self-adaptive sidelobe canceling algorithms, in particular to a radar self-adaptive sidelobe canceling algorithm.

Background

The radar has no alternative function as military equipment in modern war, interference in a radar system has the most destructive power on the detection performance of the radar, and advanced electronic interference measures and equipment are continuously emerged, so that the working electromagnetic environment of the modern radar is increasingly complicated. The various forms of interference pose a serious impact and threat to the performance of the radar. The effective anti-interference means is the condition of normal work of the radar, and accurate interference analysis is the premise of effective anti-interference. Various active and passive interferences may appear in the working environment of military radars, most of which enter a receiver by antenna side lobes, and generally radars are difficult to eliminate the side lobe active interference only by the low side lobes of antenna beams, and effective measures must be taken to suppress the side lobe interference. The adaptive sidelobe cancellation technology is one of effective measures for inhibiting radar active interference.

Disclosure of Invention

The invention aims to provide a radar self-adaptive sidelobe cancellation algorithm to solve the problems in the background art.

In order to achieve the purpose, the invention provides the following technical scheme: a radar self-adaptive sidelobe cancellation algorithm comprises a main channel and a plurality of auxiliary channels; the main channel signals are weighted by the main antenna and then synthesized, and are used for determining the target direction; the auxiliary channel signals are fed separately from each auxiliary antenna, which is typically a low gain omni-directional antenna with a gain comparable to the main antenna side lobe level. When the desired signal and the interference reach the main antenna and the auxiliary antenna simultaneously, the desired signal component in the auxiliary channel is far smaller than the desired signal component in the main channel; if the auxiliary channels are weighted and summed in real time to make up for the fixed phase difference caused by the wave path difference between the main channel and the auxiliary channel, and then the subtraction operation is carried out with the output of the main channel, the self-adaptive interference cancellation can be realized.

Preferably, the adaptive sidelobe canceling V₀Representing the destructive output, can be expressed as:wherein X represents a signal received by the main antenna; y ═ Y₁，Y₂，...，Y_N]^TRepresenting signals received by the auxiliary antenna; w ═ W₁，W₂，...，W_N]^TRepresents a weighting coefficient; "+" denotes conjugate, "H" denotes conjugate transpose, "T" denotes transpose.

Preferably, in order to minimize the total power output, a least mean square criterion is generally adopted, the mean square value of which is ξ ═ E [ | V |)₀|²]The optimal weight vector that is expanded and derived to minimize ξ is:R_XYmatrix of cross-correlation functions, R, representing main and auxiliary channels_YYA matrix of autocorrelation functions representing the secondary channels.

Preferably, the radar adaptive sidelobe canceling algorithm includes the following steps:

A. effectively selecting SLC interference sample points;

B. and (5) real-time calculation of the multi-dimensional matrix.

Preferably, the adaptive interference sampling method in step a is as follows:

a. dividing echo data of a main antenna and an auxiliary antenna in a detection distance into N sections, wherein the sampling length of each section is 32, 64, 128, 256 and the like;

b. after the main and auxiliary channel data are sampled in a segmented mode, weight coefficients of each segmented data are calculated sequentially, cancellation results of each data are obtained respectively, and the cancellation result data of each data are spliced to obtain a final cancellation processing result.

Preferably, for the problem that the number of sampling points is too large or the matrix scale is too large, and a large amount of time is consumed when the cancellation weight coefficient is calculated, parallel optimization functions are adopted in software implementation to optimize matrix operation.

Compared with the prior art, the invention has the beneficial effects that: in the invention, the main channel signals are synthesized after being weighted by the main antenna, are used for determining the target direction, and have the characteristics of strong directivity, narrow beam width, low side lobe level and the like. The auxiliary channel signals are fed separately from each auxiliary antenna, which is typically a low gain omni-directional antenna with a gain comparable to the main antenna side lobe level. When the desired signal arrives at the main and auxiliary antennas simultaneously with the interference, the desired signal component in the auxiliary channel is much smaller than the desired signal component in the main channel, while the interference magnitude is roughly comparable. If the auxiliary channels are weighted and summed in real time to make up for the fixed phase difference caused by the wave path difference between the main channel and the auxiliary channel, and then the subtraction operation is carried out with the output of the main channel, the self-adaptive interference cancellation can be realized.

Drawings

FIG. 1 is a schematic block diagram of sidelobe cancellation according to the present invention;

FIG. 2 is a schematic diagram of a segmented sampling method;

FIG. 3 is a schematic diagram showing comparison of sampling before and after cancellation during a rest period;

FIG. 4 is a schematic diagram showing comparison of sectional sampling before and after cancellation.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, the present invention provides a technical solution: a radar self-adaptive sidelobe cancellation algorithm comprises a main channel and a plurality of auxiliary channels; the main channel signals are weighted by the main antenna and then synthesized, and are used for determining the target direction; the auxiliary channel signals are fed separately from each auxiliary antenna, which is typically a low gain omni-directional antenna with a gain comparable to the main antenna side lobe level. When the desired signal and the interference reach the main antenna and the auxiliary antenna simultaneously, the desired signal component in the auxiliary channel is far smaller than the desired signal component in the main channel; if the auxiliary channels are weighted and summed in real time to make up for the fixed phase difference caused by the wave path difference between the main channel and the auxiliary channel, and then the subtraction operation is carried out with the output of the main channel, the self-adaptive interference cancellation can be realized.

In the invention, V is used for self-adaptive side lobe cancellation₀Representing the destructive output, can be expressed as:wherein X represents a signal received by the main antenna; y ═ Y₁，Y₂，...，Y_N]^TRepresenting signals received by the auxiliary antenna; w ═ W₁，W₂，...，W_N]^TRepresents a weighting coefficient; "+" denotes conjugate, "H" denotes conjugate transpose, "T" denotes transpose.

In the present invention,in order to minimize the total power output, the least mean square criterion is usually adopted, whose mean square value is ξ ═ E [ | V |)₀|²]The optimal weight vector that is expanded and derived to minimize ξ is:R_XYmatrix of cross-correlation functions, R, representing main and auxiliary channels_YYA matrix of autocorrelation functions representing the secondary channels.

When the existing radar adopts a sidelobe cancellation measure, a cancellation coefficient is calculated by adopting interference sample data in a radar resting area and is used for interference cancellation processing in a full detection distance, and the method is suitable for the condition that an interference signal is continuous in time. However, for the irregular intermittent interference released by the non-cooperative party, the sampling data of the interference signal may not be obtained in the rest area, and the calculated cancellation coefficient may not achieve the optimal cancellation effect.

Aiming at the defect that the sampling data of the interference signal is only extracted in the rest area, a method for acquiring the interference sampling data in a self-adaptive mode is provided, so that the method is suitable for the situation that the interference signal is continuous or discontinuous in time, the optimal cancellation coefficient is calculated, the optimal side lobe cancellation effect is achieved, and the detection performance is improved.

The invention discloses a radar self-adaptive sidelobe cancellation algorithm, which comprises the following steps:

A. effectively selecting SLC interference sample points;

B. and (5) real-time calculation of the multi-dimensional matrix.

The adaptive interference sampling method in the step A is as follows:

a. dividing echo data of a main antenna and an auxiliary antenna in a detection distance into N sections, wherein the sampling length of each section is 32, 64, 128, 256 and the like;

b. after the main and auxiliary channel data are sampled in a segmented mode, weight coefficients of each segmented data are calculated sequentially, cancellation results of each data are obtained respectively, and the cancellation result data of each data are spliced to obtain a final cancellation processing result.

The method for sequentially sampling the distance segments avoids the situation that the interference sample cannot be obtained, the extracted interference sample really contains interference characteristics, the calculated cancellation coefficient is more accurate, side lobe cancellation has better interference suppression capability, the anti-interference performance and the detection performance of the radar are really improved, and false alarms of the radar caused by interference are reduced.

The sampling data are extracted in a segmented mode and used for calculating the cancellation coefficient, the condition that the sampling data cannot be interfered is avoided, the method is suitable for the condition that interference signals are continuous or discontinuous in time, the influence of interference can be well restrained, and the anti-interference capability of the radar is improved.

In addition, aiming at the problems that the number of sampling points is too large or the matrix scale is too large and a large amount of time is consumed when the cancellation weight coefficient is calculated, parallel optimization functions are adopted in software implementation to optimize matrix operation.

Matlab simulation analysis

And (3) interfering a certain radar through an interference machine, storing a signal received by the radar, and performing simulation analysis on interference data.

The first method is as follows: the results of obtaining interference sample data during the rest period before and after cancellation are shown in fig. 3:

the second method comprises the following steps: interference sample data is acquired in a segmented manner, and the results before and after cancellation are shown in fig. 4.

Therefore, the anti-interference effect of the sectional sampling mode is improved compared with the sampling mode in the rest period.

In summary, in the present invention, the main channel signal is weighted by the main antenna and then synthesized for determining the target direction, and has the characteristics of strong directivity, narrow beam width, low side lobe level, and the like. The auxiliary channel signals are fed separately from each auxiliary antenna, which is typically a low gain omni-directional antenna with a gain comparable to the main antenna side lobe level. When the desired signal arrives at the main and auxiliary antennas simultaneously with the interference, the desired signal component in the auxiliary channel is much smaller than the desired signal component in the main channel, while the interference magnitude is roughly comparable. If the auxiliary channels are weighted and summed in real time to make up for the fixed phase difference caused by the wave path difference between the main channel and the auxiliary channel, and then the subtraction operation is carried out with the output of the main channel, the self-adaptive interference cancellation can be realized.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.