IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Regular Section
Direction-of-Arrival Estimation Using an Array Covariance Vector and a Reweighted l1 Norm
Xiao Yu LUOXiao chao FEILu GANPing WEIHong Shu LIAO
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2015 Volume E98.A Issue 9 Pages 1964-1967


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.

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© 2015 The Institute of Electronics, Information and Communication Engineers
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