Research on STAP matrix fusion algorithm based on LMS

Xuefei Sang; Jidong Suo; Yiyang Liu

doi:10.1117/12.2673910

6 April 2023 Research on STAP matrix fusion algorithm based on LMS

Xuefei Sang, Jidong Suo, Yiyang Liu

Proceedings Volume 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022); 1261528 (2023) https://doi.org/10.1117/12.2673910
Event: International Conference on Signal Processing and Communication Technology (SPCT 2022), 2022, Harbin, China

Abstract

The space-time adaptive processing(STAP) technique adaptively suppresses clutter jointly in the space domain and time domain, but in practice, due to the lack of sample quantity, the performance of this technique suffers a serious loss. In contrast, the knowledge-aided space-time adaptive processing(KA-STAP) algorithm can improve the estimation accuracy of the clutter covariance matrix by using a priori knowledge. In this paper, by using the cycle characteristic of the clutter covariance matrix as the priori knowledge, the spatial circular matrix, the temporal circular matrix and the spatial-temporal circular matrix are constructed. And use the Least-Mean-Square(LMS) criterion to calculate the coefficients and then integrate the above matrices. Compared with the traditional STAP method, the KA-STAP using the cyclic property as a priori knowledge has about 1 dB of output signal-to-clutter-noise(SCNR) improvement.

Citation Download Citation

Xuefei Sang, Jidong Suo, and Yiyang Liu "Research on STAP matrix fusion algorithm based on LMS", Proc. SPIE 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022), 1261528 (6 April 2023); https://doi.org/10.1117/12.2673910

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