Robust direction-of-arrival estimation based on sparse asymptotic minimum variance

This study proposes a direction-of-arrival (DOA) estimation algorithm named robust sparse asymptotic minimum variance (RSAMV) to solve the current DOA algorithms' problems, such as the difficulty in weak target estimation, low resolution and the incapacity of separating coherent signal estimati...

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Main Authors:	Xiangyu Zhang, Jun Sun, Xingrong Cao
Format:	Article
Language:	English
Published:	Wiley 2019-10-01
Series:	The Journal of Engineering
Subjects:	covariance matrices iterative methods direction-of-arrival estimation object detection current doa algorithms weak target estimation coherent signal estimation virtual weak target dynamic diagonal loading weak target loss ultra-low side lobe spatial spectrum high-resolution estimation space target coherent interference rsamv algorithm weak target detection ability samv algorithms robust direction-of-arrival estimation robust sparse asymptotic minimum variance spatial resolution ability doa estimation sampling covariance matrix iterative process bering-time recording map
Online Access:	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0720

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spelling	doaj-49325773112a40b69d89a2e97c184f802021-04-02T12:33:08ZengWileyThe Journal of Engineering2051-33052019-10-0110.1049/joe.2019.0720JOE.2019.0720Robust direction-of-arrival estimation based on sparse asymptotic minimum varianceXiangyu Zhang0Jun Sun1Xingrong Cao2Nanjing Research Institute of Electronic TechnologyThe CETC key Laboratory of IntelliSense TechnologyThe CETC key Laboratory of IntelliSense TechnologyThis study proposes a direction-of-arrival (DOA) estimation algorithm named robust sparse asymptotic minimum variance (RSAMV) to solve the current DOA algorithms' problems, such as the difficulty in weak target estimation, low resolution and the incapacity of separating coherent signal estimation. Through utilising a virtual weak target, the algorithm carries out dynamic diagonal loading to the sampling covariance matrix of SAMV in the iterative process, which effectively reduces weak target loss. Meanwhile, showing the feature of ultra-low side lobe and high sparseness, the spatial spectrum of RSAMV can easily achieve the high-resolution estimation of space target in the circumstances of coherent interference. Simulation results show that, compared with other algorithms, the RSAMV algorithm has higher spatial resolution ability and weak target detection ability. Its spatial spectrum has higher sparseness than other sparse algorithms and its performance is more robust than other SAMV algorithms. The Bering-Time Recording map processed by results that experiment on sea demonstrate the superiority of RSAMV algorithm.https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0720covariance matricesiterative methodsdirection-of-arrival estimationobject detectioncurrent doa algorithmsweak target estimationcoherent signal estimationvirtual weak targetdynamic diagonal loadingweak target lossultra-low side lobespatial spectrumhigh-resolution estimationspace targetcoherent interferencersamv algorithmweak target detection abilitysamv algorithmsrobust direction-of-arrival estimationrobust sparse asymptotic minimum variancespatial resolution abilitydoa estimationsampling covariance matrixiterative processbering-time recording map
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Xiangyu Zhang Jun Sun Xingrong Cao
spellingShingle	Xiangyu Zhang Jun Sun Xingrong Cao Robust direction-of-arrival estimation based on sparse asymptotic minimum variance The Journal of Engineering covariance matrices iterative methods direction-of-arrival estimation object detection current doa algorithms weak target estimation coherent signal estimation virtual weak target dynamic diagonal loading weak target loss ultra-low side lobe spatial spectrum high-resolution estimation space target coherent interference rsamv algorithm weak target detection ability samv algorithms robust direction-of-arrival estimation robust sparse asymptotic minimum variance spatial resolution ability doa estimation sampling covariance matrix iterative process bering-time recording map
author_facet	Xiangyu Zhang Jun Sun Xingrong Cao
author_sort	Xiangyu Zhang
title	Robust direction-of-arrival estimation based on sparse asymptotic minimum variance
title_short	Robust direction-of-arrival estimation based on sparse asymptotic minimum variance
title_full	Robust direction-of-arrival estimation based on sparse asymptotic minimum variance
title_fullStr	Robust direction-of-arrival estimation based on sparse asymptotic minimum variance
title_full_unstemmed	Robust direction-of-arrival estimation based on sparse asymptotic minimum variance
title_sort	robust direction-of-arrival estimation based on sparse asymptotic minimum variance
publisher	Wiley
series	The Journal of Engineering
issn	2051-3305
publishDate	2019-10-01
description	This study proposes a direction-of-arrival (DOA) estimation algorithm named robust sparse asymptotic minimum variance (RSAMV) to solve the current DOA algorithms' problems, such as the difficulty in weak target estimation, low resolution and the incapacity of separating coherent signal estimation. Through utilising a virtual weak target, the algorithm carries out dynamic diagonal loading to the sampling covariance matrix of SAMV in the iterative process, which effectively reduces weak target loss. Meanwhile, showing the feature of ultra-low side lobe and high sparseness, the spatial spectrum of RSAMV can easily achieve the high-resolution estimation of space target in the circumstances of coherent interference. Simulation results show that, compared with other algorithms, the RSAMV algorithm has higher spatial resolution ability and weak target detection ability. Its spatial spectrum has higher sparseness than other sparse algorithms and its performance is more robust than other SAMV algorithms. The Bering-Time Recording map processed by results that experiment on sea demonstrate the superiority of RSAMV algorithm.
topic	covariance matrices iterative methods direction-of-arrival estimation object detection current doa algorithms weak target estimation coherent signal estimation virtual weak target dynamic diagonal loading weak target loss ultra-low side lobe spatial spectrum high-resolution estimation space target coherent interference rsamv algorithm weak target detection ability samv algorithms robust direction-of-arrival estimation robust sparse asymptotic minimum variance spatial resolution ability doa estimation sampling covariance matrix iterative process bering-time recording map
url	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0720
work_keys_str_mv	AT xiangyuzhang robustdirectionofarrivalestimationbasedonsparseasymptoticminimumvariance AT junsun robustdirectionofarrivalestimationbasedonsparseasymptoticminimumvariance AT xingrongcao robustdirectionofarrivalestimationbasedonsparseasymptoticminimumvariance
_version_	1721568451356524544

Robust direction-of-arrival estimation based on sparse asymptotic minimum variance

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