Multichannel clutter suppression method based on robust principal component analysis

Abstract

The invention belongs to the technical field of multichannel clutter suppression, and particularly relates to a multichannel clutter suppression method based on robust principal component analysis. The multichannel clutter suppression method based on the robust principal component analysis comprises the following steps of obtaining a distance-Doppler image corresponding to each reception channel of radar; obtaining corresponding distance-Doppler data according to each distance-Doppler image; conducting column vectorization on distance-Doppler data matrices, and combining all column vectors into a matrix X; decomposing the matrix X through the robust principal component analysis so as to obtain a corresponding sparse matrix S0; according to the sparse matrix S0, obtaining 1 to m, wherein 1 to m are submatrices of X1 to Xm; according to 1 to m, obtaining the optimal weight wopt,j corresponding to a jth Doppler unit; conducting clutter suppression according to the optimal weight corresponding to each Doppler unit, and obtaining a result Xout after clutter suppression.

Description

technical field [0001] The invention belongs to the technical field of multi-channel clutter suppression, in particular to a multi-channel clutter suppression method based on a robust principal component analysis method. Background technique [0002] Synthetic aperture radar and moving target detection (SAR / GMTI) technology has important use value and broad application prospects in military and civilian applications, and is a hot field of radar technology research in all countries in the world. Compared with the single-channel SAR-GMTI system, the multi-channel SAR-GMTI system can effectively suppress clutter and realize the detection of slow moving targets under low signal-to-noise ratio. At present, signal processing methods based on multi-channel SAR-GMTI systems, such as Displaced Phased Center Antenna (DPCA: Displaced Phased Center Antenna), Space-Time Adaptive Processing (STAP: Space-Time Adaptive Processing) and other methods, have good heterogeneity. Wave suppressio...

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Problems solved by technology

[0004] However, most of the above methods are based on the accurate estimation of the clutter covariance matrix

However, in the actual echo data, since the energy of the moving target is small and the energy of the clutter is large, the situation that the moving target is submerged in the strong clutter background often occurs

In this environment, the information of the moving target cannot be obtained effectively, so that the data of the moving target is wrongly selected as the training sample, which eventually leads to a decrease in the output signal-to-interference-noise ratio, and even the self-cancellation phenomenon of the target.

In order to better select suitable training samples, most of the existing methods based on generalized inner product and power selection are based on data domain processing, that is, different objective functions and thresholds are set to determine where the target may be contained, and then remove it. , making the above method less practical and more complex

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