Target localization in multipath propagation environment using dictionary-based sparse representation

This paper addresses the target localization problem in complex multipath propagation environment for three-dimensional (3-D) radar systems. Firstly, an approach based on the singular value decomposition (SVD) technique is developed to reduce the data dimension and formulate the joint multiple snaps...

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Main Authors: Liu, Yuan, Liu, Hongwei, Xia, Xiang-Gen, Wang, Lu, Bi, Guoan
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/146584
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1465842021-03-02T03:53:00Z Target localization in multipath propagation environment using dictionary-based sparse representation Liu, Yuan Liu, Hongwei Xia, Xiang-Gen Wang, Lu Bi, Guoan School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Cramér-Rao Bound Direction of Arrival Estimation This paper addresses the target localization problem in complex multipath propagation environment for three-dimensional (3-D) radar systems. Firstly, an approach based on the singular value decomposition (SVD) technique is developed to reduce the data dimension and formulate the joint multiple snapshot sparse representation problem in the signal subspace domain. Subsequently, a novel sparse representation based DOA estimation algorithm, combined with alternatingly iterative and dictionary refinement techniques, is proposed. The Cramér-Rao bounds (CRB) for the target DOA and attenuation coefficient estimations of multipath model are derived in closed forms. Experimental results based on both simulated data and measured data indicate that the target localization accuracy can be effectively enhanced by utilizing the proposed algorithm in complex terrain and/or limited snapshot scenarios. Published version 2021-03-02T03:53:00Z 2021-03-02T03:53:00Z 2019 Journal Article Liu, Y., Liu, H., Xia, X.-G., Wang, L., & Bi, G. (2019). Target localization in multipath propagation environment using dictionary-based sparse representation. IEEE Access, 7, 150583-150597. doi:10.1109/access.2019.2947497 2169-3536 0000-0002-8880-3451 0000-0002-9011-9181 https://hdl.handle.net/10356/146584 10.1109/ACCESS.2019.2947497 2-s2.0-85078353513 7 150583 150597 en IEEE Access © 2019 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Cramér-Rao Bound
Direction of Arrival Estimation
spellingShingle Engineering::Electrical and electronic engineering
Cramér-Rao Bound
Direction of Arrival Estimation
Liu, Yuan
Liu, Hongwei
Xia, Xiang-Gen
Wang, Lu
Bi, Guoan
Target localization in multipath propagation environment using dictionary-based sparse representation
description This paper addresses the target localization problem in complex multipath propagation environment for three-dimensional (3-D) radar systems. Firstly, an approach based on the singular value decomposition (SVD) technique is developed to reduce the data dimension and formulate the joint multiple snapshot sparse representation problem in the signal subspace domain. Subsequently, a novel sparse representation based DOA estimation algorithm, combined with alternatingly iterative and dictionary refinement techniques, is proposed. The Cramér-Rao bounds (CRB) for the target DOA and attenuation coefficient estimations of multipath model are derived in closed forms. Experimental results based on both simulated data and measured data indicate that the target localization accuracy can be effectively enhanced by utilizing the proposed algorithm in complex terrain and/or limited snapshot scenarios.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Liu, Yuan
Liu, Hongwei
Xia, Xiang-Gen
Wang, Lu
Bi, Guoan
format Article
author Liu, Yuan
Liu, Hongwei
Xia, Xiang-Gen
Wang, Lu
Bi, Guoan
author_sort Liu, Yuan
title Target localization in multipath propagation environment using dictionary-based sparse representation
title_short Target localization in multipath propagation environment using dictionary-based sparse representation
title_full Target localization in multipath propagation environment using dictionary-based sparse representation
title_fullStr Target localization in multipath propagation environment using dictionary-based sparse representation
title_full_unstemmed Target localization in multipath propagation environment using dictionary-based sparse representation
title_sort target localization in multipath propagation environment using dictionary-based sparse representation
publishDate 2021
url https://hdl.handle.net/10356/146584
_version_ 1695706147693002752