Sparse recovery STAP method based on knowledge assistance

A sparse recovery and knowledge-assisted technology, applied in radio wave measurement systems, instruments, etc., can solve problems such as the degradation of moving target detection performance and the reduction of accurate estimation of clutter covariance matrix, so as to achieve good moving target detection effect and solve clutter Covariance matrix estimation error and the effect of overcoming the phenomenon of moving target cancellation

Active Publication Date: 2020-08-25
INNER MONGOLIA UNIV OF TECH
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Problems solved by technology

[0005] In view of the above-mentioned technical problems existing in the prior art, an embodiment of the present invention provides a knowledge-assisted sparse restoration STAP method, which can solve the problem of the existing sparse restoration-based STAP method due to grid mismatch (off-grid) and sample The existence of dense interference in the medium causes the problem of the decrease of the accurate estimation of the clutter covariance matrix and the decrease of the performance of the moving target detection

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  • Sparse recovery STAP method based on knowledge assistance
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  • Sparse recovery STAP method based on knowledge assistance

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[0055] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0056] It should be understood that various modifications may be made to the embodiments disclosed herein. Accordingly, the above description should not be viewed as limiting, but only as exemplifications of embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the application.

[0057] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the application and, together with the general description of the application given above and the detailed description of the embodiments given below, serve to explain the embodiments of the application. principle.

[0058] These and other characteristics of the present appli...

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Abstract

The invention discloses a sparse recovery STAP method based on knowledge assistance. The method comprises the following steps: constructing a sample data set; constructing a space-time steering vectormatrix of a distance unit sample; performing sparse recovery on the sample data; constructing a steering vector matrix containing prior information; judging whether the steering vector of sparse recovery corresponds to clutter or not based on the steering vector matrix containing prior information, and updating the sparse recovery vector and the dictionary based on a judgment result; performing secondary sparse recovery on the sample data based on the updated sparse recovery vector and dictionary; and performing clutter covariance matrix estimation by using the estimation sample of secondarysparse recovery. According to the method, the sparse recovery dictionary is corrected by means of sample sparse recovery and prior information of clutter distribution, clutter covariance matrix estimation errors caused by off-grid are solved. Meanwhile, the influence of dense interference in samples is removed, the moving target cancellation phenomenon is overcome, and the moving target detectionperformance is improved.

Description

technical field [0001] The invention relates to the technical field of airborne radar moving target detection, in particular to a knowledge-assisted sparse recovery STAP method. Background technique [0002] When the airborne radar detects weak and small targets on the ground / sea surface, the received strong ground / sea clutter often submerges the weak targets, which seriously affects the detection performance of airborne radar moving targets. Space-time adaptive processing (space-time adaptive processing, STAP) technology, using space-time joint processing to design a suitable filter weight vector, can effectively separate the clutter and the target in the space-time two-dimensional domain, significantly improving the The detection performance of airborne radar for moving targets. STAP technology usually requires enough independent identically distributed (IID) training samples to estimate the clutter covariance matrix. The distribution characteristics are not uniform. Th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41
CPCG01S7/415
Inventor 高志奇武志霞黄平平徐伟张振华
Owner INNER MONGOLIA UNIV OF TECH
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