A method for suppressing interference from dense false targets in multipath environments

Abstract

The present invention provides a method for suppressing dense false target interference in a multipath environment, belonging to the technical field of radar signal processing. The specific process of the method is as follows: first, the existence of dense false target interference is judged through peak detection; second, in the case of dense false target interference, the characteristic phase of the sampling point with the corresponding position number in the auxiliary channel signal is extracted according to the position number of the detected point on the channel signal, a characteristic phase vector set is constructed, the phase vector set is clustered, and for the elements in each cluster, the signal near the corresponding position is extracted to perform sidelobe cancellation processing; finally, for all the cancellation-processed signals, the amplitude of each sampling point is compared, and the sampling point with the smallest amplitude is selected as the final output, thereby realizing the suppression of dense false target interference in the multipath environment.

Description

Technical Field

[0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a method for suppressing interference from dense false targets in a multipath environment. Background Art

[0002] Dense false target jamming is a typical jamming method used against modern coherent radars. By repeatedly forwarding intercepted radar signals, it can create a series of false target peaks during radar signal processing, achieving both deception and suppression jamming effects to a certain extent.

[0003] Traditional methods for suppressing dense false target interference primarily rely on "feature recognition and elimination" and spatial domain cancellation. The former uses features from various dimensions to distinguish dense false target interference from true target signals, thereby eliminating interference. Examples include identifying the number of peaks in the interference and target signals in the fractional domain, using sidelobe blanking (SLB) to identify the signal amplitudes of the interference and target, and using frequency agility combined with waveform entropy to identify the interference and target signals in the time domain. However, these methods require either specialized system architectures or the use of multiple pulse echoes, meeting the application requirements of only certain specific scenarios. Therefore, for suppressing single-pulse dense false target interference in more conventional system architectures, spatial domain processing-based sidelobe cancellation (SLC) remains the simplest and most effective method. SLC achieves interference suppression by adaptively forming nulls in the interference direction through weighted processing of auxiliary channels, making it the most commonly used anti-interference method in modern radars.

[0004] In scenarios with multipath effects, interference signals can reach the radar receiver not only through direct paths but also through multiple reflected paths. Furthermore, because interference signals are generally high-powered, densely packed false target interference can achieve a certain coherent gain in radar signal processing, allowing it to maintain a significant interference effect even after attenuation over longer transmission distances. This is equivalent to adding multiple equivalent interference sources from different directions, resulting in insufficient degrees of freedom for system cancellation and rendering traditional SLC methods inapplicable. Summary of the Invention

[0005] In view of this, the present invention addresses the above problem and proposes a method for suppressing dense false target interference in a multipath environment to solve the problem that the existing SLC method in the above background technology cannot effectively cancel dense false target interference in a multipath environment.

[0006] In order to achieve the above object, the technical solution of the present invention is:

[0007] A method for suppressing interference from dense false targets in a multipath environment comprises the following steps:

[0008] Through peak detection, the existence of dense false target interference is judged;

[0009] In the case of dense false target interference, based on the position information of the detected point on the sum channel signal, the characteristic phase of the sampling point at the corresponding position in the auxiliary channel signal is extracted to construct a characteristic phase vector set. The detected point is the peak point where the signal amplitude is greater than the set threshold value. The sum channel signal and the auxiliary channel signal are the signals received by the sum channel and the auxiliary channel after pulse compression processing;

[0010] Clustering the phase vector set, and for each element in each cluster, extracting signals near a corresponding position to perform sidelobe cancellation processing;

[0011] For all signals after cancellation processing, the amplitude of each sampling point is compared, and the sampling point with the smallest amplitude is selected as the final output.

[0012] Furthermore, the present invention determines the presence of dense false target interference through peak detection as follows: pulse compression processing is performed on the single pulse data received by the radar system and the channel, the peak value of the processed signal is compared with a preset threshold value, and the points greater than the threshold value are defined as detected points. When the number of detected points is greater than a predetermined number, it is determined that dense false target interference exists.

[0013] Furthermore, the detected points of the present invention are:

[0014] When the sampling point after the channel pulse compression process satisfies (1), the sampling point is detected and is the detected point.

[0015]

[0016] Among them: a i Represents the amplitude of the i-th sampling point, and Thr is the preset threshold value.

[0017] Furthermore, the present invention determines whether dense false target interference exists based on the number of the detected points as follows: when the number of the detection points is greater than a set number, it is determined that dense false target interference exists, and the set number is 5-10.

[0018] Furthermore, the present invention utilizes the Kmeans method to cluster the characteristic phase vectors.

[0019] Furthermore, the present invention extracts 1 to 5 extension points near the corresponding position of the elements in each cluster and performs sidelobe cancellation processing.

[0020] Furthermore, the preset threshold value of the present invention is k times the amplitude of the signal after the channel pulse compression processing, and the value range of k is between 10 and 50.

[0021] Beneficial effects

[0022] First, the present invention is a method for suppressing dense false target interference in a multipath environment. By clustering and analyzing the characteristic phase vector, each cluster represents a path, and its members are the signal samples received on the path. Sidelobe cancellation processing is performed on each path separately, so that it can be applied to scenarios with multipath effects.

[0023] Second, the present invention uses peak detection to determine the presence of dense false target interference and distinguish signal samples from each path under multipath propagation. Based on this, the corresponding samples are selected for cancellation, and the smallest one is selected at the same distance to achieve ultimate interference suppression. This method can process single pulses for common radar systems, is simple to implement, and has practical advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 This is a schematic diagram of the dense false target interference threshold detection of the present invention;

[0026] Figure 2 Schematic diagram of the dense false target interference characteristic phase vector set of the present invention;

[0027] Figure 3 This is a schematic diagram of the results of selecting detection points for dense false target interference multipath according to the present invention;

[0028] Figure 4 This is a schematic diagram of the cancellation results of each path in the present invention;

[0029] Figure 5 Comparison of the results between the traditional method and the method of the present invention; DETAILED DESCRIPTION

[0030] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0031] It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments may be combined with each other; and, based on the embodiments in this disclosure, all other embodiments obtained by persons of ordinary skill in the art without creative work are within the scope of protection of this disclosure.

[0032] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement an apparatus and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this apparatus and / or practice this method.

[0033] The present invention proposes a method for suppressing interference from dense false targets in a multipath environment, the steps of which are as follows:

[0034] Step 1: Assume that the radar system has a sum channel and L auxiliary channels. Perform pulse compression on the single pulse data received by each radar channel. After pulse compression, the signals of each channel are recorded as S c and S n ,n=1,2,···L, each channel contains N sampling points.

[0035] Step 2: Perform threshold detection on the pulse compression results of the sum channel, such as Figure 1 As shown, the number of detected sampling points N is counted d , if N d Greater than the maximum detection point threshold N T , then it is judged that there is dense false target interference in the signal.

[0036] In the specific implementation of this step, S c The signal amplitude of each sampling point is compared with the preset threshold Thr. If the following formula (1) is satisfied, it indicates that the sampling point i is detected:

[0037]

[0038] Among them: a i Indicates the amplitude of the i-th sampling point, the threshold Thr can be set to S c k times the mean, where k is usually set between 10 and 50 based on experience.

[0039] Statistics S c The total number of detected points N d , if N d >N T , then S c There are dense false target interferences in the T It needs to be determined according to the specific radar working environment. The typical value can be set to 5 to 10.

[0040] Step 3: According to the position information of the detection point, extract the characteristic phase of the sampling point at the corresponding position in the L auxiliary channels and construct the characteristic phase vector set Φ, as shown in Figure 2 shown.

[0041] For the detected point m, assume its position number is j m ,m=1,2…N d , the signal at this sampling point can be expressed as s m =a+jb, where j is the imaginary unit, a and b are the real and imaginary parts of the sampling point signal respectively. Then the phase of the corresponding sampling points of the sum channel and the L auxiliary channels can be extracted to form the characteristic phase vector:

[0042]

[0043] in: is the corresponding channel position j m The phase at , arctan(·) represents the inverse tangent process.

[0044] For all detected points, the characteristic phase vectors are extracted to form a characteristic phase vector set:

[0045]

[0046] Step 4: Use the Kmeans method to perform cluster analysis on the characteristic phase vector set to obtain K cluster results. Each cluster represents a path, and its members are the signal samples received on the path, such as Figure 3 shown.

[0047] In the specific implementation of this step: for the characteristic phase vector set, use the Kmeans method to perform cluster analysis to distinguish the peaks of different paths. Assume that K clustering results can be obtained, and each clustering result Ψ k are all subsets of Φ and do not intersect with each other; Ψ k Contains N k members, each member is at position k l The characteristic phase vector at can be expressed as:

[0048]

[0049] Step 5: For each clustering result, for each element, extract the signal near the corresponding position and perform cancellation processing;

[0050] In order to better estimate the interference covariance in this step, the signal samples on each path are screened and SLC cancellation processing is performed according to the clustering results. During the cancellation processing, p adjacent points on the left and right of each detection point are selected for sample expansion. The expansion range p can be set to 1 to 5. In this embodiment, p = 3. The corresponding cancellation results are as follows: Figure 4 shown.

[0051] When this step is implemented, each clustering result Ψ k , for its N k members, extract the signals near the corresponding positions for cancellation processing:

[0052]

[0053] in:(·) H represents conjugate transpose, x is the matrix composed of auxiliary channel signals, R xx is the autocovariance matrix of the auxiliary channel, r xd is the mutual covariance matrix between the auxiliary channel and the main channel, E[·] represents the mean value processing, and s is the N in x k The matrix composed of detected points and their adjacent extension points,

[0054]

[0055] Step 6: For all cancellation output signals y k ,k=1,2…K, compare the amplitude of each sampling point in sequence and select the smallest one as the final output. Compared with the traditional cancellation results, this method can achieve better interference suppression performance, such as Figure 5 shown.

[0056] In this step, for each processed output, there is always a path where the false target can be suppressed well, thus having the smallest amplitude. Therefore, for all the cancellation output signals y k , k=1,2…K, compare the amplitude of each sampling point in sequence, and select the smallest one as the final output to achieve false target suppression on all paths:

[0057] S out (i)=min[y1(i) … y K (i)],i=1,2…N (7)

[0058] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for suppressing interference from dense false targets in a multipath environment, characterized in that: The following steps are involved: The presence of dense false target interference is determined through peak detection. Specifically, pulse compression processing is performed on the single pulse data received by the radar system and channel, and the processed signal is compared with a preset threshold. Points greater than the threshold are defined as detected points. When the number of detected points is greater than a predetermined number, it is determined that dense false target interference exists. In the case of dense false target interference, the characteristic phase of the sampling point at the corresponding position in the auxiliary channel signal is extracted based on the position information of the detected point on the channel signal, and the A characteristic phase vector set, wherein the detected point is a peak point where the signal amplitude is greater than a set threshold value, and the sum channel signal and the auxiliary channel signal are pulse-compressed signals received by the sum channel and the auxiliary channel; Clustering the phase vector set, and for each element in each cluster, extracting signals near a corresponding position to perform sidelobe cancellation processing; For all signals after cancellation processing, the amplitude of each sampling point is compared, and the sampling point with the smallest amplitude is selected as the final output.

2. The method for suppressing interference of dense false targets in a multipath environment according to claim 1, wherein: The detected points are: When the sampling point after the channel pulse compression process satisfies (1), the sampling point is detected and is the detected point. Among them: a i Represents the amplitude of the i-th sampling point, and Thr is the preset threshold value.

3. The method for suppressing interference of dense false targets in a multipath environment according to claim 1, wherein: When the number of the detection points is greater than a predetermined number, it is determined that there is dense false target interference, and the predetermined number is 5-10.

4. The method for suppressing interference of dense false targets in a multipath environment according to claim 1, wherein: The characteristic phase vectors are clustered using the Kmeans method.

5. The method for suppressing interference of dense false targets in a multipath environment according to claim 1, wherein: For the elements in each cluster, 1 to 5 extension points near the corresponding position are extracted to perform sidelobe cancellation processing.

6. The method for suppressing interference of dense false targets in a multipath environment according to claim 1, characterized in that: The preset threshold value is k times the amplitude of the signal after the channel pulse compression processing, and the value range of k is between 10 and 50.

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