A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array

A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array

Coherent source localization is a common problem in signal processing. In this paper, a sparse representation method is considered to deal with two-dimensional (2D) direction of arrival (DOA) estimation for coherent sources with a uniform circular array (UCA). Considering that objective function req...

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Main Authors: Xiaolong Su, Zhen Liu, Tianpeng Liu, Bo Peng, Xin Chen, Xiang Li
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2019/3849791
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spelling doaj-612cba9333494cb9b4b35463e8914e262020-11-25T01:29:08ZengHindawi LimitedInternational Journal of Antennas and Propagation1687-58691687-58772019-01-01201910.1155/2019/38497913849791A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular ArrayXiaolong Su0Zhen Liu1Tianpeng Liu2Bo Peng3Xin Chen4Xiang Li5College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCoherent source localization is a common problem in signal processing. In this paper, a sparse representation method is considered to deal with two-dimensional (2D) direction of arrival (DOA) estimation for coherent sources with a uniform circular array (UCA). Considering that objective function requires sparsity in the spatial dimension but does not require sparsity in time, singular value decomposition (SVD) is employed to reduce computational complexity and ℓ2 norm is utilized to renew objective function. After the new objective function is constructed to evaluate residual and sparsity, a second-order cone (SOC) programming is employed to solve convex optimization problem and obtain 2D spatial spectrum. Simulations show that the proposed method can deal with the case of coherent source localization, which has higher resolution than 2D MUSIC method and does not need to estimate the number of coherent sources in advance.http://dx.doi.org/10.1155/2019/3849791
collection DOAJ
language English
format Article
sources DOAJ
author Xiaolong Su
Zhen Liu
Tianpeng Liu
Bo Peng
Xin Chen
Xiang Li
spellingShingle Xiaolong Su
Zhen Liu
Tianpeng Liu
Bo Peng
Xin Chen
Xiang Li
A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array
International Journal of Antennas and Propagation
author_facet Xiaolong Su
Zhen Liu
Tianpeng Liu
Bo Peng
Xin Chen
Xiang Li
author_sort Xiaolong Su
title A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array
title_short A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array
title_full A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array
title_fullStr A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array
title_full_unstemmed A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array
title_sort sparse representation method for coherent sources angle estimation with uniform circular array
publisher Hindawi Limited
series International Journal of Antennas and Propagation
issn 1687-5869
1687-5877
publishDate 2019-01-01
description Coherent source localization is a common problem in signal processing. In this paper, a sparse representation method is considered to deal with two-dimensional (2D) direction of arrival (DOA) estimation for coherent sources with a uniform circular array (UCA). Considering that objective function requires sparsity in the spatial dimension but does not require sparsity in time, singular value decomposition (SVD) is employed to reduce computational complexity and ℓ2 norm is utilized to renew objective function. After the new objective function is constructed to evaluate residual and sparsity, a second-order cone (SOC) programming is employed to solve convex optimization problem and obtain 2D spatial spectrum. Simulations show that the proposed method can deal with the case of coherent source localization, which has higher resolution than 2D MUSIC method and does not need to estimate the number of coherent sources in advance.
url http://dx.doi.org/10.1155/2019/3849791
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