Sensors 2011, 11(9), 9098-9108; doi:10.3390/s110909098
Article

Direction-of-Arrival Estimation Based on Joint Sparsity

Received: 16 August 2011; in revised form: 17 September 2011 / Accepted: 18 September 2011 / Published: 21 September 2011
(This article belongs to the Section Physical Sensors)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: 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.
Keywords: joint-sparse; compressed sensing; Direction-of-Arrival; quasi-Newton methods; multiple measure vectors
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MDPI and ACS Style

Wang, J.; Huang, Z.; Zhou, Y. Direction-of-Arrival Estimation Based on Joint Sparsity. Sensors 2011, 11, 9098-9108.

AMA Style

Wang J, Huang Z, Zhou Y. Direction-of-Arrival Estimation Based on Joint Sparsity. Sensors. 2011; 11(9):9098-9108.

Chicago/Turabian Style

Wang, Junhua; Huang, Zhitao; Zhou, Yiyu. 2011. "Direction-of-Arrival Estimation Based on Joint Sparsity." Sensors 11, no. 9: 9098-9108.

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