DOA estimation in sparse array based on matrix completion
Jinying Gao, Yibin Rui, Yuan Gao, Yuhang Li · 2021
This paper presents a novel matrix completion algorithm, penalty decomposition method based augmented Lagrange multipliers (PD-ALM), to improve the performance of Direction Of Arrival (DOA) in sparse array. In PD-ALM algorithm, we apply the penalty decomposition method to solve low-rank matrix completion problem directly. Firstly, we reconstruct a low rank matrix using the special structure of received signals of uniform linear array (ULA). Then, PD-ALM algorithm is used to complete the received signals of the sparse array. Finally, we apply Multiple Signal Classification (MUSIC) algorithm to estimate direction of arrival. The numerical experiments are provided to validate the effectiveness of the proposed algorithm.