Direction-of-Arrival Estimation Using an Array Covariance Vector and a Reweighted l1 Norm

Xiao Yu LUO  Xiao chao FEI  Lu GAN  Ping WEI  Hong Shu LIAO  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E98-A   No.9   pp.1964-1967
Publication Date: 2015/09/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E98.A.1964
Type of Manuscript: LETTER
Category: Digital Signal Processing
Keyword: 
direction-of-arrival estimation,  sparse representation,  array covariance vector,  reweighted l1 norm,  

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Summary: 
We propose a novel sparse representation-based direction-of-arrival (DOA) estimation method. In contrast to those that approximate l0-norm minimization by l1-norm minimization, our method designs a reweighted l1 norm to substitute the l0 norm. The capability of the reweighted l1 norm to bridge the gap between the l0- and l1-norm minimization is then justified. In addition, an array covariance vector without redundancy is utilized to extend the aperture. It is proved that the degree of freedom is increased as such. The simulation results show that the proposed method performs much better than l1-type methods when the signal-to-noise ratio (SNR) is low and when the number of snapshots is small.