A training sample selection method based on united generalised inner product statistics for STAP

Abstract In heterogeneous environments, the snapshot under test (SUT) and the corresponding training samples are usually not independent and identically distributed, which seriously degrades the clutter suppression performance of space‐time adaptive processing (STAP). To solve this problem, this pap...

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Autores principales:	Xinzhe Li, Wenchong Xie, Yongliang Wang
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/e615d71be8a640f4a1ba72a8c2497f3b
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spelling	oai:doaj.org-article:e615d71be8a640f4a1ba72a8c2497f3b2021-11-12T15:34:29ZA training sample selection method based on united generalised inner product statistics for STAP1751-87921751-878410.1049/rsn2.12146https://doaj.org/article/e615d71be8a640f4a1ba72a8c2497f3b2021-12-01T00:00:00Zhttps://doi.org/10.1049/rsn2.12146https://doaj.org/toc/1751-8784https://doaj.org/toc/1751-8792Abstract In heterogeneous environments, the snapshot under test (SUT) and the corresponding training samples are usually not independent and identically distributed, which seriously degrades the clutter suppression performance of space‐time adaptive processing (STAP). To solve this problem, this paper proposes a method which can select the training samples with similar clutter characteristics to that of the SUT. The proposed method constructs a novel united generalised inner product (UGIP) statistic with the sub‐aperture clutter covariance matrix (CCM) of the SUT and that of any other snapshot. The smaller the statistic is, the more similar the corresponding two snapshots are. Therefore, the snapshots with smaller UGIPs will be selected as training samples. The proposed method effectively improves the quality of the selected training samples for STAP and a better estimate of the CCM can be obtained. Simulation experiments verify the effectiveness of the proposed method with both simulated data and measured data.Xinzhe LiWenchong XieYongliang WangWileyarticleTelecommunicationTK5101-6720ENIET Radar, Sonar & Navigation, Vol 15, Iss 12, Pp 1565-1572 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Telecommunication TK5101-6720
spellingShingle	Telecommunication TK5101-6720 Xinzhe Li Wenchong Xie Yongliang Wang A training sample selection method based on united generalised inner product statistics for STAP
description	Abstract In heterogeneous environments, the snapshot under test (SUT) and the corresponding training samples are usually not independent and identically distributed, which seriously degrades the clutter suppression performance of space‐time adaptive processing (STAP). To solve this problem, this paper proposes a method which can select the training samples with similar clutter characteristics to that of the SUT. The proposed method constructs a novel united generalised inner product (UGIP) statistic with the sub‐aperture clutter covariance matrix (CCM) of the SUT and that of any other snapshot. The smaller the statistic is, the more similar the corresponding two snapshots are. Therefore, the snapshots with smaller UGIPs will be selected as training samples. The proposed method effectively improves the quality of the selected training samples for STAP and a better estimate of the CCM can be obtained. Simulation experiments verify the effectiveness of the proposed method with both simulated data and measured data.
format	article
author	Xinzhe Li Wenchong Xie Yongliang Wang
author_facet	Xinzhe Li Wenchong Xie Yongliang Wang
author_sort	Xinzhe Li
title	A training sample selection method based on united generalised inner product statistics for STAP
title_short	A training sample selection method based on united generalised inner product statistics for STAP
title_full	A training sample selection method based on united generalised inner product statistics for STAP
title_fullStr	A training sample selection method based on united generalised inner product statistics for STAP
title_full_unstemmed	A training sample selection method based on united generalised inner product statistics for STAP
title_sort	training sample selection method based on united generalised inner product statistics for stap
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/e615d71be8a640f4a1ba72a8c2497f3b
work_keys_str_mv	AT xinzheli atrainingsampleselectionmethodbasedonunitedgeneralisedinnerproductstatisticsforstap AT wenchongxie atrainingsampleselectionmethodbasedonunitedgeneralisedinnerproductstatisticsforstap AT yongliangwang atrainingsampleselectionmethodbasedonunitedgeneralisedinnerproductstatisticsforstap AT xinzheli trainingsampleselectionmethodbasedonunitedgeneralisedinnerproductstatisticsforstap AT wenchongxie trainingsampleselectionmethodbasedonunitedgeneralisedinnerproductstatisticsforstap AT yongliangwang trainingsampleselectionmethodbasedonunitedgeneralisedinnerproductstatisticsforstap
_version_	1718430405981372416

A training sample selection method based on united generalised inner product statistics for STAP

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