2-D DOA Estimation Under Mainlobe Jamming Based on Subarray Level Blind Source Separation

To address the problem of difficult direction of arrival (DOA) estimation of targets under mainlobe jamming, this paper proposes a two-dimensional (2-D) DOA estimation algorithm based on subarray level blind source separation (BSS). Firstly, using the subarray sliding window configuration, the planar array is divided into subarrays with consistent phase differences. Then, for the mixed signals received by each subarray, the subarray level BSS algorithm is used to separate target echoes and jamming signals. Finally, based on the phase difference between target echoes estimated by each subarray, the multiple signal classification (MUSIC) algorithm is used for 2-D DOA estimation. The numerical simulation results show that the proposed algorithm can effectively separate targets and jamming, and also has good performance in 2-D DOA estimation.