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Sensors 2015, 15(11), 29721-29733; doi:10.3390/s151129721

A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations

College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 17 July 2015 / Revised: 12 November 2015 / Accepted: 17 November 2015 / Published: 24 November 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [712 KB, uploaded 24 November 2015]   |  

Abstract

In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV) to deal with the MMV problem. MMV problem can be changed to single measurement vector (SMV) problem by using the linear combination of eigenvectors of array covariance matrix in signal subspace as a new SMV for sparse solution calculation. So the complexity of this proposed algorithm is smaller than other DOA estimation algorithms of MMV. Meanwhile, it can overcome the limitation of the conventional sparsity-based DOA estimation approaches that the unknown directions belong to a predefined discrete angular grid, so it can further improve the DOA estimation accuracy. The modified Rife algorithm for DOA estimation (MRife-DOA) is simulated based on SRBWEV algorithm. In this proposed algorithm, the largest and sub-largest inner products between the measurement vector or its residual and the atoms in the dictionary are utilized to further modify DOA estimation according to the principle of Rife algorithm and the basic idea of coarse-to-fine estimation. Finally, simulation experiments show that the proposed algorithm is effective and can reduce the DOA estimation error caused by grid effect with lower complexity. View Full-Text
Keywords: direction of arrival (DOA) estimation; sparse representations; eigenvalue decomposition (EVD); off-grid; Rife algorithm direction of arrival (DOA) estimation; sparse representations; eigenvalue decomposition (EVD); off-grid; Rife algorithm
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. (CC BY 4.0).

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Chen, T.; Wu, H.; Guo, L.; Liu, L. A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations. Sensors 2015, 15, 29721-29733.

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