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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Format: | Article |
Language: | English |
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China Science Publishing & Media Ltd. (CSPM)
2014-04-01
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Series: | Leida xuebao |
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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. |
first_indexed | 2024-03-09T08:41:15Z |
format | Article |
id | doaj.art-bac8bb1838064f9cb19f00cd27d044e3 |
institution | Directory Open Access Journal |
issn | 2095-283X 2095-283X |
language | English |
last_indexed | 2024-03-09T08:41:15Z |
publishDate | 2014-04-01 |
publisher | China Science Publishing & Media Ltd. (CSPM) |
record_format | Article |
series | Leida xuebao |
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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