Adaptive null broadening beamforming of uniform rectangular array based on interference plus noise covariance matrix reconstruction

Yu Zhao; Bin Yang; Chongyi Yue

doi:10.1117/12.2660053

3 February 2023 Adaptive null broadening beamforming of uniform rectangular array based on interference plus noise covariance matrix reconstruction

Yu Zhao, Bin Yang, Chongyi Yue

Author Affiliations +

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251116 (2023) https://doi.org/10.1117/12.2660053
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Null broadening is an effective method to suppress the motion interference, but most methods are suitable for the uniform linear array. To solve this problem, an adaptive null broadening method based on uniform rectangular array (URA) is proposed in this paper. The method first estimates the power of interference and adds virtual interference with the same power near the real interference. Then, the method estimates the noise power and reconstructs the interference plus noise covariance matrix (INCM) which contains the null broadening information. Finally, the desired signal steering vector is corrected to obtain the optimal weighting vector. Simulation results show that the method can form wide nulls in the interference direction to suppress the motion interference and is robust to the desired signal steering vector mismatch.

Citation Download Citation

Yu Zhao, Bin Yang, and Chongyi Yue "Adaptive null broadening beamforming of uniform rectangular array based on interference plus noise covariance matrix reconstruction", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251116 (3 February 2023); https://doi.org/10.1117/12.2660053

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