Mixed targets localization using symmetric nested frequency diverse array radar
Abstract A mixed near‐field and far‐field targets localization method based on sparse signal reconstruction and subspace method is presented, which can obtain both direction‐of‐arrival (DOA) and range information of the targets by utilizing symmetric nested frequency diverse array (SNFDA). Due to th...
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Wiley
2021-02-01
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Online Access: | https://doi.org/10.1049/sil2.12009 |
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author | Hui Chen Wen‐Qin Wang Wei Wang |
author_facet | Hui Chen Wen‐Qin Wang Wei Wang |
author_sort | Hui Chen |
collection | DOAJ |
description | Abstract A mixed near‐field and far‐field targets localization method based on sparse signal reconstruction and subspace method is presented, which can obtain both direction‐of‐arrival (DOA) and range information of the targets by utilizing symmetric nested frequency diverse array (SNFDA). Due to the frequency diverse array (FDA) owing time‐angle‐range‐dependent beampattern, the authors first properly design frequency increments and choose the sensor outputs to construct a fourth‐order cumulant matrix of SNFDA which is only related to DOAs of targets, and the authors estimate the DOAs of all targets by solving the ℓ1‐norm minimization convex optimization problem. Then a mixed range‐dependent overcomplete dictionary with DOAs estimation is formulated in the compressive sensing framework to classify targets types by using periodic characteristics of the estimated range‐dependent beampattern. Finally, the range estimations of all targets are obtained via 1‐D range‐domain spectral searching. Compared with the existing mixed near‐field and far‐field targets localization methods, the proposed method jointly uses FDA angle‐range‐dependent beampattern and increased degrees‐of‐freedom of nested array, which can achieve both improved resolutions and accuracies in DOAs and ranges estimation for all targets. A set of numerical examples is reported and discussed to validate the superiority of the proposed algorithm. |
format | Article |
id | doaj-art-e14cbad57d1f421cb1f8e565bbe9c45b |
institution | Kabale University |
issn | 1751-9675 1751-9683 |
language | English |
publishDate | 2021-02-01 |
publisher | Wiley |
record_format | Article |
series | IET Signal Processing |
spelling | doaj-art-e14cbad57d1f421cb1f8e565bbe9c45b2025-02-03T06:47:26ZengWileyIET Signal Processing1751-96751751-96832021-02-0115111310.1049/sil2.12009Mixed targets localization using symmetric nested frequency diverse array radarHui Chen0Wen‐Qin Wang1Wei Wang2School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu Sichuan ChinaSchool of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu Sichuan ChinaSchool of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu Sichuan ChinaAbstract A mixed near‐field and far‐field targets localization method based on sparse signal reconstruction and subspace method is presented, which can obtain both direction‐of‐arrival (DOA) and range information of the targets by utilizing symmetric nested frequency diverse array (SNFDA). Due to the frequency diverse array (FDA) owing time‐angle‐range‐dependent beampattern, the authors first properly design frequency increments and choose the sensor outputs to construct a fourth‐order cumulant matrix of SNFDA which is only related to DOAs of targets, and the authors estimate the DOAs of all targets by solving the ℓ1‐norm minimization convex optimization problem. Then a mixed range‐dependent overcomplete dictionary with DOAs estimation is formulated in the compressive sensing framework to classify targets types by using periodic characteristics of the estimated range‐dependent beampattern. Finally, the range estimations of all targets are obtained via 1‐D range‐domain spectral searching. Compared with the existing mixed near‐field and far‐field targets localization methods, the proposed method jointly uses FDA angle‐range‐dependent beampattern and increased degrees‐of‐freedom of nested array, which can achieve both improved resolutions and accuracies in DOAs and ranges estimation for all targets. A set of numerical examples is reported and discussed to validate the superiority of the proposed algorithm.https://doi.org/10.1049/sil2.12009array signal processingconvex programmingdirection-of-arrival estimationhigher order statisticsoptimisationsignal reconstruction |
spellingShingle | Hui Chen Wen‐Qin Wang Wei Wang Mixed targets localization using symmetric nested frequency diverse array radar IET Signal Processing array signal processing convex programming direction-of-arrival estimation higher order statistics optimisation signal reconstruction |
title | Mixed targets localization using symmetric nested frequency diverse array radar |
title_full | Mixed targets localization using symmetric nested frequency diverse array radar |
title_fullStr | Mixed targets localization using symmetric nested frequency diverse array radar |
title_full_unstemmed | Mixed targets localization using symmetric nested frequency diverse array radar |
title_short | Mixed targets localization using symmetric nested frequency diverse array radar |
title_sort | mixed targets localization using symmetric nested frequency diverse array radar |
topic | array signal processing convex programming direction-of-arrival estimation higher order statistics optimisation signal reconstruction |
url | https://doi.org/10.1049/sil2.12009 |
work_keys_str_mv | AT huichen mixedtargetslocalizationusingsymmetricnestedfrequencydiversearrayradar AT wenqinwang mixedtargetslocalizationusingsymmetricnestedfrequencydiversearrayradar AT weiwang mixedtargetslocalizationusingsymmetricnestedfrequencydiversearrayradar |