Direction-of-Arrival Estimation Based on Joint Sparsity

We present a DOA estimation algorithm, called Joint-Sparse DOA to address the problem of direction-of-arrival (DOA) estimation using sensor arrays. Firstly, DOA estimation is cast as the joint-sparse recovery problem. Then, norm is approximated by an arctan function to represent joint sparsity and DOA estimation can be obtained by minimizing the approximate norm. Finally, the minimization problem is solved by a 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 resolution, and it can also handle the coherent sources well.