Compressive Sensing-based DOA Estimation using the Dantzig Selector

In this paper, a new compressive sensing (CS)-based direction of arrival (DOA) estimation technique using the Dantzig selector is proposed. The proposed scheme can identify more source signals than the number of sensors used, without requiring an a priori knowledge of the number of source signals to be estimated and without any constraint or assumption about the nature of the signal sources using a fewer number of snapshots. The performance of the proposed scheme is compared to that of the Zhang penalty-based algorithm and the MVDR A-LASSO DOA estimation technique. The computational complexity of the proposed algorithm is substantially lower than that of the Zhang penalty-based method or MVDR A-LASSO.