Space-time adaptive processing method under non-homogeneous clutter environment

Abstract

The invention discloses a space-time adaptive processing method under a non-homogeneous clutter environment, belonging to the technical field of airborne radar clutter suppression. The method comprises the following steps: extracting a snapshot training sample x1 along a distance direction, asking for a clutter space-time two-dimensional spectrum, and inducing a sparse solution in a clutter covariance matrix to be estimated; weighting the clutter covariance matrix to be estimated; calculating the corresponding space-time adaptive filtering device according to the estimated covariance matrix, and judging whether a moving-target exists at an output end. The invention aims to the shortage of IID training samples under the non-homogeneous clutter environment, and uses the method represented by complete sparse way to super-resolvably estimate the clutter space-time two-dimensional spectrum, thereby releasing the clutter covariance matrix estimated by a single-frame training sample. The invention can effectively avoid the rapid variation of landform caused by dispersing clutter sources, and is robust for the space-time spectrum dispersion caused by factors of the external movement of the clutter simultaneously, different channels and the like. Mountaintop real data demonstrates that the method can maintain good performance of the clutter suppression, and suitably for the strong non-homogeneous clutter environment.

Description

technical field The invention relates to a space-time adaptive (STAP) processing method in a non-uniform clutter environment, which is a STAP framework CS-STAP based on sparse clutter estimation, and uses the prior knowledge of sparse clutter distribution to super-resolution estimate clutter Space-time two-dimensional spectrum (space-time spectrum), and then realize the method of estimating the clutter covariance matrix with a small number of training samples, so as to achieve the purpose of improving the estimation convergence speed, belonging to the technical field of airborne radar clutter suppression. Background technique Aiming at the lack of independent and identically distributed (IID) training samples in the actual non-uniform clutter environment, the present invention proposes a method of using Sparse Overcomplete Representations (Sparse Overcomplete Representations) to estimate the clutter space-time spectrum with high resolution with a small number of training samp...

AI Technical Summary

Problems solved by technology

However, the existing non-uniform detectors (NHD) also need to pre-estimate the clutter covariance matrix, and cannot avoid the problem of clutter statistical information estimation, and if there is an error in the estimated clutter covariance, it will also The decisions of non-uniform detectors affect the

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