CN115267695A - Dense false target interference suppression method in multipath environment - Google Patents

Dense false target interference suppression method in multipath environment Download PDF

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CN115267695A
CN115267695A CN202210575675.3A CN202210575675A CN115267695A CN 115267695 A CN115267695 A CN 115267695A CN 202210575675 A CN202210575675 A CN 202210575675A CN 115267695 A CN115267695 A CN 115267695A
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dense
false target
interference
points
detected
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王长杰
周超
杨志芬
陈宇翔
刘泉华
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Bit Raco Electronic Information Technology Co ltd
Beijing Institute of Technology BIT
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract

The invention provides a dense false target interference suppression method in a multipath environment, which belongs to the technical field of radar signal processing and comprises the following specific processes: firstly, judging the existence of dense false target interference through peak value detection; secondly, aiming at the condition that dense false target interference exists, aiming at the position serial numbers of detected points on the sum channel signal, extracting the characteristic phase of sampling points of corresponding position serial numbers in the auxiliary channel signal, constructing a characteristic phase vector set, clustering the phase vector set, and extracting signals near corresponding positions for side lobe cancellation processing aiming at elements in each cluster; and finally, comparing the amplitude of each sampling point of all the signals subjected to cancellation processing, and selecting the sampling point with the minimum amplitude as final output to realize the dense false target interference suppression in the multipath environment.

Description

Dense false target interference suppression method in multipath environment
Technical Field
The invention belongs to the technical field of radar signal processing, and particularly relates to a method for suppressing dense false target interference in a multipath environment.
Background
Dense decoy interference is a typical interference that counters modern coherent radar. By forwarding intercepted radar signals for many times, a series of false target peak values can be formed in the radar signal processing process, and the interference effects of deception and suppression can be achieved to a certain extent.
Aiming at the suppression of dense false target interference, the traditional method mainly comprises two ways based on feature recognition and elimination and airspace cancellation. The former distinguishes dense false target interference and real target signals through characteristics of various dimensions so as to eliminate interference, such as identifying the number of peaks of interference and target signals in a fractional domain, identifying the signal amplitude of the interference and target by using side lobe masking (SLB) or identifying the time domain of the interference and target signals by using a method of combining frequency agility with waveform entropy, and the like. However, these methods either require a special system architecture or require the use of multiple pulsed echoes, which can only meet the application requirements of certain specific scenarios. Therefore, for single-pulse dense false target interference suppression under a more conventional system, side-lobe cancellation (SLC) based on spatial domain processing is still the simplest and most effective method. The SLC forms a zero point in an interference direction in a self-adaptive mode through auxiliary channel weighting processing, interference suppression is achieved, and the method is the most common anti-interference method of modern radars.
For a scene with a multipath effect, an interference signal enters a radar receiver through a direct path and can be received by a radar through a plurality of reflection paths; meanwhile, because the interference signal generally has stronger power, the dense false target interference can also obtain certain coherent gain in radar signal processing, and therefore, the interference effect can still be obvious even after transmission attenuation for a longer distance. This is equivalent to adding a plurality of different incoming equivalent interferences, resulting in a system with insufficient cancellation freedom, and the conventional SLC method is no longer applicable.
Disclosure of Invention
In view of the above, the present invention provides a method for suppressing interference of dense decoys in a multipath environment, so as to solve the problem that the conventional SLC method in the background art cannot effectively cancel interference of dense decoys in a multipath environment.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a method for suppressing dense false target interference in a multipath environment comprises the following steps:
judging the existence of the interference of the dense false target through peak value detection;
aiming at the condition that dense false target interference exists, aiming at the position information of a detected point on a sum channel signal, extracting the characteristic phase of a sampling point at a corresponding position in an auxiliary channel signal, and constructing a characteristic phase vector set, wherein the detected point is a peak point with a signal amplitude larger than a set threshold value, and the sum channel signal and the auxiliary channel signal are signals which are received by a sum channel and an auxiliary channel and are subjected to pulse compression processing;
clustering the phase vector sets, and extracting signals near corresponding positions for side lobe cancellation processing aiming at elements in each cluster;
and comparing the amplitude of each sampling point of all the signals subjected to cancellation processing, and selecting the sampling point with the minimum amplitude as final output.
Further, the determining the existence of the dense false target interference through the peak detection in the present invention is: the method comprises the steps of carrying out pulse compression processing on monopulse data received by a radar system and a channel, comparing a processed signal peak value with a preset threshold value, defining points larger than the threshold value as detected points, and judging that dense false target interference exists when the number of the detected points is larger than a preset number.
Further, the detected points of the invention are:
when the sampling point after the channel pulse compression processing satisfies (1), the sampling point is detected as a detected point,
Figure BDA0003658873810000031
wherein: a is aiIndicating the amplitude of the ith sample point, thr, is a predetermined threshold value.
Further, the determining whether there is dense decoy interference based on the number of detected points in the present invention is: and when the number of the detection points is greater than the set number, judging that the dense false target interference exists, wherein the set number is 5-10.
Further, the invention utilizes a Kmeans method to cluster the characteristic phase vectors.
Furthermore, the invention extracts 1-5 extension points near the corresponding positions for the elements in each cluster to perform side lobe cancellation processing.
Furthermore, the preset threshold value is k times of the amplitude of the signal after the channel pulse compression processing, and the value range of k is between 10 and 50.
Advantageous effects
Firstly, the invention relates to a dense false target interference suppression method under a multipath environment, each cluster represents a path by clustering analysis of characteristic phase vectors, members in the cluster are signal samples received on the path, and sidelobe cancellation processing is respectively carried out on each path, so that the method can be suitable for scenes with multipath effects.
Secondly, the invention judges the existence of the interference of the dense false target through peak value detection, distinguishes signal samples of each path under multipath propagation, selects corresponding samples to cancel on the basis and realizes the final interference suppression through same distance selection. The method can be used for processing the single pulse aiming at the radar with the common system, is simple to realize and has application advantages.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of the dense decoy interference threshold detection of the present invention;
FIG. 2 is a schematic diagram of a dense decoy interference characteristic phase vector set according to the present invention;
FIG. 3 is a schematic diagram showing the selection result of dense false target interference multi-path detection points;
FIG. 4 is a schematic diagram of the result of each path individual cancellation according to the present invention;
FIG. 5 is a comparison of cancellation results for the conventional method and the method of the present invention;
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be noted that, in the case of no conflict, the features in the following embodiments and examples may be combined with each other; moreover, all other embodiments that can be derived by one of ordinary skill in the art from the embodiments disclosed herein without making any creative effort fall within the scope of the present disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the disclosure, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. Additionally, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
The invention provides a dense false target interference suppression method in a multipath environment, which comprises the following steps:
the method comprises the following steps: the radar system is provided with a sum channel and L auxiliary channels, pulse compression is carried out on monopulse data received by each channel of the radar, and each channel is subjected to pulse compression processingSignals are respectively marked as ScAnd SnN =1,2, · · L, each channel containing N sampling points.
Step two: performing threshold detection on the sum channel pulse compression result, counting the number N of detected sampling points as shown in FIG. 1dIf N is presentdGreater than a maximum checkpoint threshold NTThen the signal is judged to have dense decoy interference.
When the step is implemented, S iscComparing the signal amplitude of each sampling point with a preset threshold Thr, and if the signal amplitude satisfies the following formula (1), indicating that the sampling point i is detected:
Figure BDA0003658873810000051
wherein: a isiRepresenting the magnitude of the ith sample point, the threshold Thr may be set to ScK times the mean value, and k is typically set empirically between 10 and 50.
Statistics ScNumber N of all detected pointsdIf N is presentd>NTThen, explain ScIn the presence of dense decoy interference, where NTA typical value may be set to 5-10, as may be required depending on the particular radar operating environment.
Step three: according to the position information of the detection points, extracting the characteristic phases of the sampling points at corresponding positions in the L auxiliary channels, and constructing a characteristic phase vector set phi, as shown in FIG. 2.
For the detected point m, assume its position number is jm,m＝1,2…NdThe signal at the sampling point can be represented as smAnd = a + jb, wherein j is an imaginary unit, and a and b are the real part and the imaginary part of the sampling point signal respectively. The phases of their sum channel and the corresponding sample points of the L auxiliary channels can be extracted to form a characteristic phase vector:
Figure BDA0003658873810000052
wherein: phi is a*j,*∈[c 1…L]For the corresponding channel position jmThe phase at (c), arctan (·) represents the inverse tangent process.
And (3) extracting characteristic phase vectors aiming at all detected points to form a characteristic phase vector set:
Figure BDA0003658873810000063
step four, performing cluster analysis by using a Kmeans method aiming at the characteristic phase vector set to obtain K cluster results, wherein each cluster represents a path, and members in the cluster are signal samples received on the path, as shown in fig. 3.
The method comprises the following specific steps: and (4) performing clustering analysis by using a Kmeans method aiming at the characteristic phase vector set so as to distinguish the peak values of different paths. Assuming that K clustering results are available, each clustering result ΨkAre all subsets of Φ and are disjoint from each other; ΨkIn which contains NkA member, each member being a position klThe characteristic phase vector of (a) can be expressed as:
Figure BDA0003658873810000061
step five, aiming at each clustering result, extracting signals near corresponding positions for each element of each clustering result to perform cancellation processing;
in the step, in order to better estimate the interference covariance, signal samples on each path are screened according to a clustering result and subjected to SLC cancellation processing; in the cancellation process, p adjacent points on the left and right of each detection point are selected for sample expansion, the expansion range p may be set to 1 to 5, in this embodiment, p =3, and the corresponding cancellation result is shown in fig. 4.
When the step is implemented specifically, every clustering result ΨkFor N thereofkEach member, extracting signals near the corresponding position for cancellation processing:
Figure BDA0003658873810000062
wherein: (.)HRepresenting a conjugate transpose, x being a matrix formed by the auxiliary channel signals, RxxAs the autocovariance matrix of the auxiliary channel, rxdIs a cross covariance matrix of the secondary channel and the primary channel, E [ ·]Denotes the averaging process, s is N in xkA matrix of detected points and their neighboring extension points,
Figure BDA0003658873810000071
step six, outputting the signal y for all the cancellationkK =1,2 … K, the amplitudes of each sampling point are compared in sequence, and the smallest amplitude is selected as the final output, so that compared with the traditional cancellation result, the method can obtain better interference suppression performance, as shown in fig. 5.
In this step, for each processing output, the decoys on one path can be better suppressed, so as to have the minimum amplitude. Thus, the output signal y is output for all cancellationskK =1,2 … K, the amplitudes of each sampling point are compared in sequence, and the smallest amplitude is selected as the final output, so that the false target suppression on all paths can be realized:
Sout(i)＝min[y1(i)…yK(i)],i＝1,2…N (7)
in summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1. A method for suppressing interference of dense false targets in a multipath environment is characterized by comprising the following steps:
judging the existence of the interference of the dense false target through peak value detection;
aiming at the condition that dense false target interference exists, aiming at the position information of a detected point on a sum channel signal, extracting the characteristic phase of a sampling point at a corresponding position in an auxiliary channel signal, and constructing a characteristic phase vector set, wherein the detected point is a peak point with a signal amplitude larger than a set threshold value, and the sum channel signal and the auxiliary channel signal are signals which are received by a sum channel and an auxiliary channel and are subjected to pulse compression processing;
clustering the phase vector sets, and extracting signals near corresponding positions for side lobe cancellation processing aiming at elements in each cluster;
and comparing the amplitude of each sampling point of all the signals subjected to cancellation processing, and selecting the sampling point with the minimum amplitude as final output.
2. The method according to claim 1, wherein the determining the existence of the dense decoy interference through peak detection comprises: the method comprises the steps of carrying out pulse compression processing on monopulse data received by a radar system and a channel, comparing a processed signal with a preset threshold value, defining points larger than the threshold value as detected points, and judging that dense false target interference exists when the number of the detected points is larger than a preset number.
3. The method for suppressing interference of dense decoys in multipath environment as claimed in claim 2, wherein said detected points are:
when the sampling point after the channel pulse compression processing satisfies (1), the sampling point is detected as a detected point,
Figure FDA0003658873800000011
wherein: a isiIndicating the amplitude of the ith sample point, thr, is a predetermined threshold value.
4. The method according to claim 1, wherein the determining whether there is dense decoy interference based on the number of detected points is: and when the number of the detection points is larger than the set number, judging that dense false target interference exists, wherein the set number is 5-10.
5. The method according to claim 1, wherein the eigenphase vectors are clustered by using a Kmeans method.
6. The method according to claim 1, wherein for each cluster element, 1-5 spread points near the corresponding position are extracted for side-lobe cancellation.
7. The method according to claim 1, wherein the preset threshold is k times of the amplitude of the signal after the channel pulse compression processing, and the value of k ranges from 10 to 50.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117233734A (en) * 2023-11-14 2023-12-15 山东富锐光学科技有限公司 Laser radar data acquisition method and system based on TDC and ADC and laser radar

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117233734A (en) * 2023-11-14 2023-12-15 山东富锐光学科技有限公司 Laser radar data acquisition method and system based on TDC and ADC and laser radar

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