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...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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Wiley
2021-12-01
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Series: | IET Radar, Sonar & Navigation |
Subjects: | |
Online Access: | https://doi.org/10.1049/rsn2.12146 |
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author | Xinzhe Li Wenchong Xie Yongliang Wang |
author_facet | Xinzhe Li Wenchong Xie Yongliang Wang |
author_sort | Xinzhe Li |
collection | DOAJ |
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. |
first_indexed | 2024-04-12T05:08:45Z |
format | Article |
id | doaj.art-e615d71be8a640f4a1ba72a8c2497f3b |
institution | Directory Open Access Journal |
issn | 1751-8784 1751-8792 |
language | English |
last_indexed | 2024-04-12T05:08:45Z |
publishDate | 2021-12-01 |
publisher | Wiley |
record_format | Article |
series | IET Radar, Sonar & Navigation |
spelling | doaj.art-e615d71be8a640f4a1ba72a8c2497f3b2022-12-22T03:46:49ZengWileyIET Radar, Sonar & Navigation1751-87841751-87922021-12-0115121565157210.1049/rsn2.12146A training sample selection method based on united generalised inner product statistics for STAPXinzhe Li0Wenchong Xie1Yongliang Wang2Key research Lab Wuhan Early Warning Academy Wuhan ChinaKey research Lab Wuhan Early Warning Academy Wuhan ChinaKey research Lab Wuhan Early Warning Academy Wuhan ChinaAbstract 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.https://doi.org/10.1049/rsn2.12146airborne radarobject detectioncovariance matricesradar signal processingradar clutterspace‐time adaptive processing |
spellingShingle | Xinzhe Li Wenchong Xie Yongliang Wang A training sample selection method based on united generalised inner product statistics for STAP IET Radar, Sonar & Navigation airborne radar object detection covariance matrices radar signal processing radar clutter space‐time adaptive processing |
title | 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_short | 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 |
topic | airborne radar object detection covariance matrices radar signal processing radar clutter space‐time adaptive processing |
url | https://doi.org/10.1049/rsn2.12146 |
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