CN111123252A - Parameter adjustable direction detection method during signal mismatching in clutter environment - Google Patents

Parameter adjustable direction detection method during signal mismatching in clutter environment Download PDF

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CN111123252A
CN111123252A CN201911377389.0A CN201911377389A CN111123252A CN 111123252 A CN111123252 A CN 111123252A CN 201911377389 A CN201911377389 A CN 201911377389A CN 111123252 A CN111123252 A CN 111123252A
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刘维建
王永良
杜庆磊
陈辉
戴灵燕
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Air Force Early Warning Academy
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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 detection method for detecting an extended target during signal mismatching in a clutter environment, which comprises the following steps: respectively carrying out quasi-whitening on the signal matrix and the data to be detected by using the sampling covariance matrix; determining an initial value of an adjustable parameter; constructing detection statistics by using the signal matrix after the quasi-whitening and the data to be detected after the quasi-whitening according to the signal subspace dimension and the target extension dimension; comparing the detection statistic with a detection threshold: if the detection statistic is larger than the detection threshold, judging that the target exists; otherwise, the target is judged to be absent. The invention has flexible mismatch signal detection capability, can realize the inhibition of mismatch signals and the steady detection of the mismatch signals; meanwhile, the method has the characteristic of constant false alarm, and no additional constant false alarm processing step is needed.

Description

Parameter adjustable direction detection method during signal mismatching in clutter environment
Technical Field
The invention relates to an extended target detection method in signal mismatching in a clutter environment, which is particularly suitable for a multi-channel active phased array radar.
Background
Target detection is one of the most basic, primary functions of radar. As radar performance increases, the resolution of the radar continues to increase, and targets tend to exhibit extended characteristics in the distance dimension, particularly for large targets such as strategic bombers or large sea-level ships. In addition, due to the existence of array element errors and interference signals, a signal mismatch phenomenon often exists in practice, namely that the assumed value of the system is inconsistent with the true value.
The target detection required will vary depending on the cause of the signal mismatch. If the signal mismatch is caused by array element errors, a detection method with robust performance is required. Conversely, if the signal mismatch is caused by interference, a detection method having a mismatch sensitive characteristic is required. The existing detection method has fixed detection performance on mismatch performance, and cannot adjust the detection characteristic on mismatch signals according to requirements.
Disclosure of Invention
The invention aims to solve the problem of extended target detection when signal mismatch exists in a clutter environment, and designs a detection method with flexible regulation and control characteristics on the mismatch signal.
The invention provides the following technical scheme, and discloses a detection method for an extended target during signal mismatching in a clutter environment, which comprises the following steps:
respectively carrying out quasi-whitening on the signal matrix and the data to be detected by using the sampling covariance matrix;
determining an initial value of an adjustable parameter;
constructing detection statistics by using the signal matrix after the quasi-whitening and the data to be detected after the quasi-whitening according to the signal subspace dimension and the target extension dimension;
comparing the detection statistic with a detection threshold: if the detection statistic is larger than the detection threshold, judging that the target exists; otherwise, the target is judged to be absent.
Further, in the quasi-whitening of the signal matrix and the data to be detected respectively by using the sampling covariance matrix, the sampling covariance matrix is:
Figure RE-GDA0002412581480000021
wherein x islIs the first oneTraining samples with dimension Nx 1, N being number of system channels, L being number of training samples, superscript (·)HRepresenting a conjugate transpose operation.
Further, the signal matrix and the data to be detected are subjected to quasi-whitening respectively by utilizing the sampling covariance matrix, and the quasi-whitening of the signal matrix and the data to be detected is respectively realized by the following two formulas:
Figure BDA0002341343140000022
and
Figure BDA0002341343140000023
wherein S is-1/2＝UΛ-1/2UHU is a feature matrix of S, obtained by feature decomposition,
Figure BDA0002341343140000024
diag (. circle.) denotes a diagonal matrix, λnAnd H is an Nth characteristic value of S, an Nxp dimensional signal matrix and X is N X K dimensional data to be detected.
Further, according to the determination of the initial value of the adjustable parameter: when the system needs to use robust detection, the system selects between [0,0.5 ]; when the system needs mismatch sensitive detection, the selection is between [1.1 and 2.5 ].
Further, according to the signal subspace dimension and the target extension dimension, constructing detection statistics by using the signal matrix after the quasi-whitening and the data to be detected after the quasi-whitening: when the signal subspace dimension is greater than or equal to the target extension dimension, the expression of the detection statistic is:
Figure RE-GDA0002412581480000024
when the signal subspace dimension is smaller than the target extension dimension, the expression of the detection statistic is:
Figure RE-GDA0002412581480000025
wherein λ ismax[·]Maximum eigenvalue of the representation matrix, superscript (. cndot.)HRepresents the conjugate transpose of the matrix and,
Figure RE-GDA0002412581480000026
IKrepresenting a K by K dimensional identity matrix, superscript (. smallcircle.)-1The inverse of the matrix is represented and gamma represents the adjustable parameter.
Further, adjusting an adjustable parameter according to a judgment result: when mismatch sensitive detection is needed and a target cannot be detected, the adjustable parameters are properly reduced; when robust detection is required and the detected target signal is strong, the adjustable parameters are appropriately increased.
Compared with the prior art, the invention has the beneficial effects that:
1. the detection method designed by the invention has flexible performance on the detection of the mismatch signal, and can realize the inhibition of the mismatch signal and the steady detection of the mismatch signal by setting different adjustable parameters;
2. because the signal matrix and the data to be detected are subjected to quasi-whitening by using the sampling covariance matrix, the detection method designed by the invention has the constant false alarm characteristic, and an additional constant false alarm processing step is not needed;
3. because the detection method does not contain independent filtering and constant false alarm processing processes, the detection method designed by the invention has a simple structure, and can adjust the detection statistic parameter setting through the feedback of a judgment result so as to further improve the detection performance.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart of a method for detecting a direction adjustable parameter when a signal is mismatched in a clutter environment according to the present invention.
Detailed Description
Preferred embodiments of the invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the invention, and do not limit the scope of the invention.
Referring to fig. 1, a method for detecting an extended target in a clutter environment when a signal is mismatched includes the following steps: respectively whitening the signal matrix and the data to be detected by using a sampling covariance matrix; determining an initial value of an adjustable parameter; constructing detection statistics by using the signal matrix after the quasi-whitening and the data to be detected after the quasi-whitening according to the signal subspace dimension and the target expansion dimension; comparing the detection statistic with a detection threshold: if the detection statistic is larger than the detection threshold, judging that the target exists; otherwise, the target is determined to be absent.
Assuming that an nx1-dimensional steering vector s of an extended target is located in a subspace spanned by an nxp-dimensional column full rank matrix H, s may be expressed as H θ, wherein the px1-dimensional column vector θ represents coordinates of a signal steering vector in the subspaceH+ N, where K1 dimensional column vector α represents the amplitude information of the target at different distances, superscript (. cndot.)HThe method comprises the steps of representing a conjugate transposition operation, representing the sum of a thermal noise component and a clutter component in data to be detected by an NxK dimensional matrix N, independently distributing each column of N in the same way, obeying Gaussian distribution with a mean value of zero and a covariance matrix of R, in practical application, theta, α and R are unknown, and in order to estimate R, a certain amount of training sample data is neededl＝nlWherein n islIs the sum of the clutter and thermal noise components in the ith training sample.
Based on the system parameters, the detailed steps of the invention are as follows:
according to the method, in the process of respectively carrying out quasi-whitening on a signal matrix and data to be detected by utilizing a sampling covariance matrix, an NxN dimensional sampling covariance matrix constructed by training samples is as follows:
Figure BDA0002341343140000042
wherein x islThe first training sample with dimension Nx 1, N the number of system channels, L the number of training samples, and superscript
Figure BDA0002341343140000043
Representing a conjugate transpose operation.
And the quasi-whitening of the signal matrix and the data to be detected is realized by the following two formulas respectively:
Figure BDA0002341343140000044
and
Figure BDA0002341343140000045
wherein S is-1/2＝UΛ-1/2UHU is a feature matrix of S, obtained by feature decomposition,
Figure BDA0002341343140000046
diag (. circle.) denotes a diagonal matrix, λnAnd H is an Nth characteristic value of S, an Nxp dimensional signal matrix and X is N X K dimensional data to be detected.
According to the determination of the initial value of the adjustable parameter, the step is carried out in two situations: when the system needs to use robust detection, the system selects between [0,0.5 ]; when the system needs mismatch sensitive detection, it selects between [1.1,2.5 ].
According to the signal subspace dimension and the target extension dimension, constructing detection statistics by using the signal matrix after the quasi-whitening and the data to be detected after the quasi-whitening: when the signal subspace dimension is greater than or equal to the target extension dimension, the expression of the detection statistic is:
Figure RE-GDA0002412581480000051
when the signal subspace dimension is smaller than the target extension dimension, the expression of the detection statistic is:
Figure RE-GDA0002412581480000052
wherein λ ismax[·]Maximum eigenvalue of the representation matrix, superscript (. cndot.)HRepresents the conjugate transpose of the matrix and,
Figure RE-GDA0002412581480000053
IKrepresenting a K x K dimensional unit matrix, superscript (.)-1The inverse of the matrix is represented and gamma represents the adjustable parameter.
Adjusting adjustable parameters according to two conditions of a judgment result: when mismatch sensitive detection is needed and a target cannot be detected, the adjustable parameters are properly reduced; when robust detection is required and the detected target signal is strong, the adjustable parameters are appropriately increased.
Determining a detection threshold by using Monte Carlo simulation, comparing the detection statistic with the detection threshold, and judging that a target exists if the detection statistic is larger than the detection threshold; otherwise, the target is judged to be absent.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (6)

1. A detection method for extended target detection in signal mismatch in clutter environment is characterized in that: the method comprises the following steps:
respectively carrying out quasi-whitening on the signal matrix and the data to be detected by using the sampling covariance matrix;
determining an initial value of an adjustable parameter;
constructing detection statistics by using the signal matrix after the quasi-whitening and the data to be detected after the quasi-whitening according to the signal subspace dimension and the target extension dimension;
comparing the detection statistic with a detection threshold: if the detection statistic is larger than the detection threshold, judging that the target exists; otherwise, the target is judged to be absent.
2. The method of claim 1 wherein the adaptive direction detection of the signal mismatch parameters is based on the use of a sampling covariance matrixIn the quasi-whitening of the number matrix and the data to be detected, the sampling covariance matrix is as follows:
Figure RE-FDA0002412581470000011
wherein x islIs the ith training sample with dimension Nx 1, N is the number of system channels, L is the number of training samples, superscript (. cndot.)HRepresenting a conjugate transpose operation.
3. The method according to claim 1, wherein the signal matrix and the data to be detected are quasi-whitened according to a sampling covariance matrix, and the quasi-whitening is performed according to the following two equations:
Figure FDA0002341343130000013
and
Figure FDA0002341343130000014
wherein S is-1/2＝UΛ-1/2UHU is a feature matrix of S, obtained by feature decomposition,
Figure FDA0002341343130000015
diag (. circle.) denotes a diagonal matrix, λnAnd H is an Nth characteristic value of S, an Nxp dimensional signal matrix and X is N X K dimensional data to be detected.
4. The method according to claim 1, wherein the method comprises, in response to determining the initial value of the adjustable parameter: when the system needs to use robust detection, the system selects between [0,0.5 ]; when the system needs mismatch sensitive detection, the selection is between [1.1 and 2.5 ].
5. The method according to claim 1, wherein the direction-adjustable signal parameters are determined based on the subspace dimension of the signal and the target extension dimension,constructing detection statistics by using the signal matrix after the quasi-whitening and the data to be detected after the quasi-whitening: when the signal subspace dimension is greater than or equal to the target extension dimension, the expression of the detection statistic is:
Figure RE-FDA0002412581470000021
when the signal subspace dimension is smaller than the target extension dimension, the expression of the detection statistic is:
Figure RE-FDA0002412581470000022
wherein λ ismax[·]Maximum eigenvalue of the representation matrix, superscript (. cndot.)HRepresents the conjugate transpose of the matrix and,
Figure RE-FDA0002412581470000023
IKrepresenting a K by K dimensional identity matrix, superscript (. smallcircle.)-1The inverse of the matrix is represented and gamma represents the adjustable parameter.
6. The method according to claim 1, wherein the adjustable direction of the parameter when the signal mismatch occurs in the clutter environment is adjusted according to the decision result: when mismatch sensitive detection is needed and the target cannot be detected, the adjustable parameters are properly reduced; when robust detection is required and the detected target signal is strong, the adjustable parameters are appropriately increased.
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CN112558014A (en) * 2021-02-23 2021-03-26 中国人民解放军空军预警学院 Method and system for detecting adjustable subspace of extended target parameters in clutter
CN112558034A (en) * 2021-02-23 2021-03-26 中国人民解放军空军预警学院 Extended target sensitive detector and system during subspace signal mismatch
CN112834999A (en) * 2020-12-29 2021-05-25 中国人民解放军空军预警学院 Radar target constant false alarm detection method and system when interference direction is known
CN113030932A (en) * 2021-02-05 2021-06-25 中国人民解放军空军预警学院 Robust adaptive detection method and system for extended target
CN113030928A (en) * 2021-02-05 2021-06-25 中国人民解放军空军预警学院 Polarization radar extended target self-adaptive detection method and system in non-uniform environment
CN113238211A (en) * 2021-02-05 2021-08-10 中国人民解放军空军预警学院 Parameterized adaptive array signal detection method and system under interference condition
CN115980729A (en) * 2022-12-30 2023-04-18 中国人民解放军空军预警学院 Adjustable detection method and system for extended target parameters under signal mismatch
CN115980729B (en) * 2022-12-30 2024-05-14 中国人民解放军空军预警学院 Adjustable detection method and system for extended target parameters under signal mismatch

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CN112834999A (en) * 2020-12-29 2021-05-25 中国人民解放军空军预警学院 Radar target constant false alarm detection method and system when interference direction is known
CN112834999B (en) * 2020-12-29 2022-06-28 中国人民解放军空军预警学院 Radar target constant false alarm detection method and system when interference direction is known
CN113030932A (en) * 2021-02-05 2021-06-25 中国人民解放军空军预警学院 Robust adaptive detection method and system for extended target
CN113030928A (en) * 2021-02-05 2021-06-25 中国人民解放军空军预警学院 Polarization radar extended target self-adaptive detection method and system in non-uniform environment
CN113238211A (en) * 2021-02-05 2021-08-10 中国人民解放军空军预警学院 Parameterized adaptive array signal detection method and system under interference condition
CN113238211B (en) * 2021-02-05 2022-05-10 中国人民解放军空军预警学院 Parameterized adaptive array signal detection method and system under interference condition
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CN112558034A (en) * 2021-02-23 2021-03-26 中国人民解放军空军预警学院 Extended target sensitive detector and system during subspace signal mismatch
CN115980729A (en) * 2022-12-30 2023-04-18 中国人民解放军空军预警学院 Adjustable detection method and system for extended target parameters under signal mismatch
CN115980729B (en) * 2022-12-30 2024-05-14 中国人民解放军空军预警学院 Adjustable detection method and system for extended target parameters under signal mismatch

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