非凸松弛原子范数空时动目标参数估计算法

doi:10.12305/j.issn.1001-506X.2023.09.14

Abstract

Abstract:

The performance of the sparse recovery-based parameter estimation methods for moving target in space-time adaptive processing (STAP) degrades significantly in the case of dictionary mismatch. A space-time moving target parameter estimation based on non-convex relaxation of atomic norm is proposed. According to continuous compressed sensing and low rank matrix recovery theorems, the estimation of azimuth and velocity for moving target are obtained with high accuracy and super resolution, which utilizes the intrinsically sparse characteristic of moving target echo in the angle-Doppler domain. The proposed method can avoid the dictionary mismatch problem in the sparse recovery, and improves the performance of parameter estimation effectively. Numerical results show that compared with the existing grid-based approaches and atomic norm minimization approach, this approach has higher estimation accuracy and allows closely spaced targets to be more easily distinguished.

Key words: space-time adaptive processing (STAP), moving target parameter estimation, sparse recovery, dictionary mismatch, non-convex atomic norm

CLC Number:

TN959.73

Ran LAI, Gang SUN, Wei ZHANG, Tao ZHANG. Space-time moving target parameter estimation algorithm based on non-convex relaxation of atomic norm[J]. Systems Engineering and Electronics, 2023, 45(9): 2761-2767.

Figures/Tables 7

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References 20

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Space-time moving target parameter estimation algorithm based on non-convex relaxation of atomic norm

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