Enhanced covariances matrix sparse representation method for DOA estimation

An enhanced covariances sparse representation method for direction-of-arrival (DOA) estimation is proposed. The method can estimate coherent sources with low computation complexity. The cross-Kronecker product terms of the steering vector are introduced as an extra basis to improve the sparse model. Based on the enhanced model and iteration operation, the proposed method has greater precision in multiple coherent sources situations. Compared with several existing DOA estimation methods, simulation experiments have validated the effectiveness of the proposed method.