Direction-Of-Arrival Estimation Based On Joint Sparse Recovery

Abstract

For the problem of Direction-Of-Arrival (DOA) Estimation using sensor arrays, we present a DOA estimation algorithm, called Joint-Sparse DOA. Firstly, DOA estimation is cast as the joint-sparse recovery problem. Then, norm is approximated by arctan function to express joint sparsity and DOA estimation can be obtained by minimizing approximate norm. Finally, the minimization problem is solved by quasi-Newton method to estimate DOA. Simulation results show that our algorithm has some advantages over most existing methods: it needs a small number of snapshots to estimate DOA, while the number of sources need not be known a priori. Besides, it improves the probability of resolution, and it can also handle the correlated sources well.