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CN110988831B - Parameter adjustable detector for signal mismatch in clutter and interference coexistence environment - Google Patents

Parameter adjustable detector for signal mismatch in clutter and interference coexistence environment Download PDF

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CN110988831B
CN110988831B CN201910352071.0A CN201910352071A CN110988831B CN 110988831 B CN110988831 B CN 110988831B CN 201910352071 A CN201910352071 A CN 201910352071A CN 110988831 B CN110988831 B CN 110988831B
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CN110988831A (en
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刘维建
段克清
王永良
杜庆磊
张昭建
柳成荫
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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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures

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Abstract

The invention discloses a target detection method for solving the problem of signal mismatching of a multi-channel airborne active phased array radar in a clutter and interference coexistence environment. The method introduces adjustable parameters, and realizes flexible detection of the mismatch signals by adjusting the adjustable parameters. Firstly, a sampling covariance matrix is formed by utilizing a training sample, then the sampling covariance matrix is used for carrying out quasi-whitening on data to be detected, an interference matrix and a signal matrix, and the interference matrix, the signal matrix and the data to be detected after the quasi-whitening are utilized to combine adjustable parameters to form a parameter adjustable detector. The detector designed by the invention can simultaneously realize clutter suppression, interference suppression and target detection, has the constant false alarm characteristic, does not need additional constant false alarm processing steps, can flexibly detect mismatched signals, and can realize steady detection of the mismatched signals by reducing adjustable parameters while suppressing clutter and interference; conversely, the mismatch signal can be suppressed by increasing the adjustable parameter.

Description

Parameter adjustable detector for signal mismatch in clutter and interference coexistence environment
Technical Field
The invention relates to a parameter adjustable detector for signal mismatch in a clutter and interference coexistence environment, which is particularly suitable for a multi-channel airborne active phased array radar.
Background
The airborne radar can overcome the influence of the curvature of the earth and provide earlier early warning time due to the fact that the airborne platform is lifted off. However, the movement of the airborne radar causes the Doppler frequency of the ground sea clutter of the radar to be seriously broadened, and the intensity of the ground sea clutter is large, so that the detection performance of the airborne radar is seriously influenced. Meanwhile, the working environment of the airborne radar is often interfered by enemy, other co-frequency radars of the own party or interference caused by industrial production. In addition, due to the reason of radar antenna array processing and installation industry, the radar antenna often has array errors, so that signal mismatch is caused, namely the actual guide vector of the target is inconsistent with the assumed value of the system. Therefore, in order to achieve effective target detection, the airborne radar must simultaneously overcome clutter and interference, and take into account the adverse effects of signal mismatch.
Disclosure of Invention
The invention aims to solve the problem of target detection of a multi-channel airborne active phased array radar in signal mismatch in a clutter and interference coexistence environment.
In order to achieve the above object, the present invention provides a design method of a parameter adjustable detector, which comprises the following steps:
(1) forming a sampling covariance matrix by using the training samples;
(2) carrying out quasi-whitening on data to be detected, an interference matrix and a signal matrix by using a sampling covariance matrix;
(3) forming an orthogonal projection matrix orthogonal to the interference by using the interference matrix after the quasi-whitening;
(4) calculating the projection of the signal matrix after the quasi-whitening in a projection space orthogonal to the interference, and calculating an orthogonal projection matrix of the projection;
(5) calculating the energy of the data to be detected after the quasi-whitening in a projection space orthogonal to the interference;
(6) calculating the energy of the data to be detected after the quasi-whitening in the orthogonal projection space in the step (4);
(7) determining adjustable parameters according to system requirements, and forming a parameter adjustable detector by using results in the steps (5) and (6);
(8) and calculating a detection threshold and comparing the detection threshold with the detection statistic of the detector, judging that the target exists if the detection statistic is greater than the detection threshold, and otherwise judging that the target does not exist.
The invention has the advantages that:
(1) the detector designed by the invention can simultaneously realize clutter suppression, interference suppression and target detection.
(2) The detector designed by the invention has the constant false alarm characteristic, and does not need additional constant false alarm processing steps.
(3) The detector designed by the invention can flexibly detect the mismatched signals, and can realize steady detection of the mismatched signals by reducing adjustable parameters while inhibiting clutter and interference; conversely, the mismatch signal can be suppressed by increasing the adjustable parameter.
Drawings
Fig. 1 is a block diagram of the structure of an embodiment of the present invention. The processing procedures of sampling covariance matrix calculation, quasi-whitening processing, orthogonal projection matrix calculation and the like in the graph can be realized on a general programmable signal processing board in a programming way.
Detailed Description
The principle of implementing the invention is as follows: forming a sampling covariance matrix by using training samples received by an airborne radar, and performing quasi-whitening processing on data to be detected, a signal matrix and an interference matrix by using the sampling covariance matrix to eliminate clutter; selecting reasonable adjustable parameters, and forming detection statistics of a detector by using the data after the quasi-whitening; determining a detection threshold according to a preset false alarm probability; and comparing the detection statistic of the detector with the detection threshold, judging that the target exists if the former is higher than the latter, and otherwise, judging that the target does not exist.
The detailed steps of the invention are as follows:
(1) for an airborne radar with N antenna channels, echo data of front and rear L distance units to be detected are utilized to form a sampling covariance matrix
Figure BSA0000182484500000021
Wherein x islIs the l training sample with dimension Nx 1, N is the systemNumber of channels, L number of training samples, superscript (. cndot.)HIs a conjugate transpose.
(2) And (3) carrying out quasi-whitening on the data x to be detected, the interference matrix J and the signal matrix H by using a sampling covariance matrix S, namely:
Figure BSA0000182484500000022
wherein S is-1/2＝UΛ-1/2UHU is unitary matrix in S characteristic decomposition, and Λ ═ diag (λ)1，λ2，...，λN) For corresponding diagonal matrices, λnN is 1,2, …, N, diag (·) represents a diagonal matrix,
Figure BSA0000182484500000023
x is Nx1 dimension data to be detected, J is an Nxq dimension interference matrix, and H is an Nxp dimension signal matrix.
(3) Using quasi-whitened interference matrices
Figure BSA0000182484500000024
Forming an orthogonal projection matrix orthogonal to the interference, wherein the expression is as follows:
Figure BSA0000182484500000025
(4) computing a signal matrix after quasi-whitening
Figure BSA0000182484500000026
Projecting in a projection space orthogonal to the interference and calculating an orthogonal projection matrix of the projection, expressed as
Figure BSA0000182484500000027
(5) Calculating quasi-whitened data to be detected
Figure BSA0000182484500000028
The energy in the projection space orthogonal to the interference is expressed by
Figure BSA0000182484500000029
(6) Calculating quasi-whitened data to be detected
Figure BSA00001824845000000210
The energy in the orthogonal projection space in the step (4) is expressed by
Figure BSA0000182484500000031
(7) Determining adjustable parameters according to system requirements, and forming a parameter adjustable detector by using the results in the steps (5) and (6), wherein the expression is
Figure BSA0000182484500000032
Wherein, k is a non-negative adjustable parameter, if the detector is expected to have a steady detection characteristic to the mismatch signal, the adjustable parameter can be selected in the interval 0 & lt k & lt 1, and the smaller k is, the more the detector is steady; if the detector is expected to have mismatch sensitivity to mismatch signals (i.e., suppress mismatch signals), the tunable parameter should satisfy k > 1, and the larger k, the more mismatch sensitive the detector, but k should not be too large, and the range k < 3 should be satisfied.
(8) The detection threshold eta is calculated by a numerical method shown as the following formula
Figure BSA0000182484500000033
Wherein PFA represents a preset false alarm probability,
Figure BSA0000182484500000034
eta is the detection threshold, and is the detection threshold,
Figure BSA0000182484500000035
(. The)! Represents a factorial; delta beta and betaiThe calculation is divided into the following three cases:
a. when k is 0. ltoreq. k.ltoreq.1 and η > 1
Figure BSA0000182484500000036
b. When k is greater than 1 and eta is less than or equal to 1
Figure BSA0000182484500000037
c. When k > 1 and η > 1
Figure BSA0000182484500000038
After obtaining the detection threshold, the detection threshold is compared with the detection statistic t of the detectorDetectorAnd comparing, if the detection statistic is larger than the detection threshold, judging that the target exists, otherwise, judging that the target does not exist.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various changes or modifications within the scope of the appended claims.

Claims (2)

1. The detector with adjustable parameters when signals are mismatched in a clutter and interference coexistence environment comprises the following technical steps:
(1) forming a sampling covariance matrix by using the training samples;
(2) carrying out quasi-whitening on data to be detected, an interference matrix and a signal matrix by using a sampling covariance matrix;
(3) forming an orthogonal projection matrix orthogonal to the interference by using the interference matrix after the quasi-whitening;
(4) calculating the projection of the signal matrix after the quasi-whitening in a projection space orthogonal to the interference, and calculating an orthogonal projection matrix of the projection;
(5) calculating the energy of the data to be detected after the quasi-whitening in a projection space orthogonal to the interference;
(6) calculating the energy of the data to be detected after the quasi-whitening in the orthogonal projection space in the step (4);
(7) determining adjustable parameters according to system requirements, and forming a parameter adjustable detector by using results in the steps (5) and (6);
(8) calculating a detection threshold and comparing the detection threshold with detection statistics of a detector, judging that a target exists if the detection statistics are larger than the detection threshold, and otherwise judging that the target does not exist;
the sampling covariance matrix in step (1) is
Figure FDA0003636166790000011
Wherein x islIs the L training sample with dimension N × 1, N is the number of system channels, L is the number of training samples,upper label (.) H Is a conjugate transpose;
the results of the quasi-whitening of the data to be detected, the interference matrix and the signal matrix in the step (2) are respectively
Figure FDA0003636166790000012
Figure FDA0003636166790000013
And
Figure FDA0003636166790000014
wherein S is-1/2＝UΛ-1/2UHU is unitary matrix in S characteristic decomposition, and Λ ═ diag (λ)1，λ2,.., N) are the corresponding diagonal momentsMatrix, λnN is 1,2, …, N, diag (·) denotes a diagonal matrix,
Figure FDA0003636166790000015
x is Nx1-dimensional data to be detected, J is an Nxq-dimensional interference matrix, and H is an Nxp-dimensional signal matrix;
calculating the projection of the quasi-whitened signal matrix in the projection space orthogonal to the interference in the step (4), and calculating the orthogonal projection matrix of the projection, wherein the expression is
Figure FDA0003636166790000016
Wherein,
Figure FDA0003636166790000017
calculating the energy of the quasi-whitened data to be detected in the projection space orthogonal to the interference in the step (5), wherein the expression is
Figure FDA0003636166790000018
Calculating the energy of the data to be detected after the quasi-whitening in the orthogonal projection space in the step (4) in the step (6), wherein the expression is
Figure FDA0003636166790000019
The expression of the parameter adjustable detector in the step (7) is
Figure FDA0003636166790000021
Wherein, k is a non-negative adjustable parameter, if the detector is expected to have a steady detection characteristic to the mismatch signal, the adjustable parameter is selected in the interval 0 & lt k & lt 1, and the smaller k is, the more the detector is steady; if the detector is expected to have mismatch sensitivity to the mismatch signal, i.e. suppress the mismatch signal, the adjustable parameter needs to satisfy k > 1, and the larger k, the more mismatch sensitive the detector, but k should not be too large, and the range k < 3 needs to be satisfied.
2. The tunable parameter detector for signal mismatch in clutter and interference co-existence environment as claimed in claim 1, wherein the detection threshold in step (8) is obtained by a numerical search method, i.e. the detection threshold is obtained by using a numerical search method
Figure FDA0003636166790000022
Wherein PFA represents a preset false alarm probability,
Figure FDA0003636166790000023
eta is the detection threshold, and is the detection threshold,
Figure FDA0003636166790000024
(. The | is! Represents a factorial;
delta beta and betaiThe calculation is divided into the following three cases:
a. when k is 0. ltoreq. k.ltoreq.1 and η > 1
Figure FDA0003636166790000025
b. When k is greater than 1 and eta is less than or equal to 1
Figure FDA0003636166790000026
c. When k > 1 and η > 1
Figure FDA0003636166790000027
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CN111948634A (en) * 2020-07-19 2020-11-17 中国人民解放军空军预警学院 Target detection method and device based on covariance matrix reconstruction under interference condition
CN112835000B (en) * 2020-12-29 2022-05-20 中国人民解放军空军预警学院 Self-adaptive detection method under non-uniform clutter and interference condition
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
CN112558015B (en) * 2021-02-23 2021-09-07 中国人民解放军空军预警学院 Method and system for interference suppression before self-adaptive detection in complex electromagnetic environment
CN112799022B (en) * 2021-04-08 2021-07-06 中国人民解放军空军预警学院 Extended target detection method and system in non-uniform and interference environment
CN113267758B (en) * 2021-07-16 2021-09-24 中国人民解放军空军预警学院 Target detection method and system in presence of interference in composite Gaussian environment
CN116112323B (en) * 2021-11-10 2024-06-07 大唐移动通信设备有限公司 Interference suppression method, device, equipment and storage medium
CN116819480B (en) * 2023-07-17 2024-05-24 中国人民解放军空军预警学院 Self-adaptive target detection method and system in strong clutter of airborne radar

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