Direction-of-Arrival Estimation Based on Joint Sparsity

Sensors

Junhua Wang¹  Zhitao Huang² 

[1] School of Electronic Science and Engineering, NUDT, Changsha 410073, China;

关键词: joint-sparse;    compressed sensing;    Direction-of-Arrival;    quasi-Newton methods;    multiple measure vectors;   

DOI  :  10.3390/s110909098

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.