A multiple measurement vector approach for DOA estimation

被引：0

作者：

Hosseini S.M. ^{[1
]}

Sadeghzadeh R.A. ^{[1
]}

机构：

[1] Faculty of Electrical Engineering, K.N.Toosi University of Technology, Tehran

来源：

Recent Advances in Electrical and Electronic Engineering | 2017年 / 10卷 / 03期

关键词：

Compressed sensing; Direction of arrival; Multiple measurement vector; Non-uniform linear array; Novel algorithm; Signal processing;

D O I：

10.2174/2352096510666170601092534

中图分类号：

学科分类号：

摘要：

Background: Compressed Sensing (CS) is an emerging signal processing technique for signal acquisition and reconstruction which recently finds applications in array processing. Direction of Arrival (DOA) is a well-known problem in array signal processing which can be treated with methods based on compressed sensing. Methods: In this work, a novel algorithm has been developed based on sparse multiple measurement vector model (MMV) to estimate DOAs of far-field and narrowband sources in linear arrays scenarios. The proposed algorithm exploits singular value decomposition denoising to enhance the reconstruction process. Conclusion: Several simulations have been carried out to show the superior performance of proposed method in comparison to simultaneous orthogonal matching pursuit (S-OMP), l2,1 minimization and root-MUISC in both uniform linear array (ULA) and nonuniform linear array (NLA) scenarios. © 2017 Bentham Science Publishers.

引用

页码：216 / 222

页数：6

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