A Space-time Adaptive Processing Algorithm Based on Joint Sparse Recovery

Sparse recovery Space-Time Adaptive Processing (STAP) methods for obtaining the clutter spectrum require few training samples and can effectively suppress clutter in nonhomogeneous clutter environments. However, presently available sparse recovery STAP methods only use single training samples to rec...

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Main Authors: Duan Ke-qing, Wang Ze-tao, Xie Wen-chong, Gao Fei, Wang Yong-liang
Format: Article
Language:English
Published: China Science Publishing & Media Ltd. (CSPM) 2014-04-01
Series:Leida xuebao
Subjects:
Online Access:http://radars.ie.ac.cn/EN/abstract/abstract168.shtml#
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author Duan Ke-qing
Wang Ze-tao
Xie Wen-chong
Gao Fei
Wang Yong-liang
author_facet Duan Ke-qing
Wang Ze-tao
Xie Wen-chong
Gao Fei
Wang Yong-liang
author_sort Duan Ke-qing
collection DOAJ
description Sparse recovery Space-Time Adaptive Processing (STAP) methods for obtaining the clutter spectrum require few training samples and can effectively suppress clutter in nonhomogeneous clutter environments. However, presently available sparse recovery STAP methods only use single training samples to recover the clutter spectrum, neglecting information from multiple samples. Moreover, the recovery performance of the abovementioned methods is sensitive to noise. In this study, a subspace-based jointly sparse recovery method is proposed. The information from multiple training samples is fully used and robust clutter suppression performance in noisy environments is achieved. Simulation results show the effectiveness of the proposed method.
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spelling doaj.art-bac8bb1838064f9cb19f00cd27d044e32023-12-02T16:47:22ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2095-283X2014-04-013222923410.3724/SP.J.1300.2014.13149A Space-time Adaptive Processing Algorithm Based on Joint Sparse RecoveryDuan Ke-qing0Wang Ze-tao1Xie Wen-chong2Gao Fei3Wang Yong-liang4Air Force Early Warning AcademyAir Force Early Warning AcademyAir Force Early Warning AcademyAir Force Early Warning AcademyAir Force Early Warning AcademySparse recovery Space-Time Adaptive Processing (STAP) methods for obtaining the clutter spectrum require few training samples and can effectively suppress clutter in nonhomogeneous clutter environments. However, presently available sparse recovery STAP methods only use single training samples to recover the clutter spectrum, neglecting information from multiple samples. Moreover, the recovery performance of the abovementioned methods is sensitive to noise. In this study, a subspace-based jointly sparse recovery method is proposed. The information from multiple training samples is fully used and robust clutter suppression performance in noisy environments is achieved. Simulation results show the effectiveness of the proposed method.http://radars.ie.ac.cn/EN/abstract/abstract168.shtml#Space-Time Adaptive Processing (STAP)Joint sparse recoverySubspaceGreedy algorithm
spellingShingle Duan Ke-qing
Wang Ze-tao
Xie Wen-chong
Gao Fei
Wang Yong-liang
A Space-time Adaptive Processing Algorithm Based on Joint Sparse Recovery
Leida xuebao
Space-Time Adaptive Processing (STAP)
Joint sparse recovery
Subspace
Greedy algorithm
title A Space-time Adaptive Processing Algorithm Based on Joint Sparse Recovery
title_full A Space-time Adaptive Processing Algorithm Based on Joint Sparse Recovery
title_fullStr A Space-time Adaptive Processing Algorithm Based on Joint Sparse Recovery
title_full_unstemmed A Space-time Adaptive Processing Algorithm Based on Joint Sparse Recovery
title_short A Space-time Adaptive Processing Algorithm Based on Joint Sparse Recovery
title_sort space time adaptive processing algorithm based on joint sparse recovery
topic Space-Time Adaptive Processing (STAP)
Joint sparse recovery
Subspace
Greedy algorithm
url http://radars.ie.ac.cn/EN/abstract/abstract168.shtml#
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