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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Main Authors: Hui Chen, Wen‐Qin Wang, Wei Wang
Format: Article
Language:English
Published: Wiley 2021-02-01
Series:IET Signal Processing
Subjects:
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.
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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