TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode

Maritime ship detection is an essential prerequisite for targeting key objectives and safeguarding the security of territorial waters. The all-day and all-weather operational capability of synthetic aperture radar (SAR) makes SAR-based ship detection indispensable for maritime surveillance. Marine s...

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Main Authors: Chaoyue Liu, Yunkai Deng, Zhimin Zhang, Huaitao Fan, Heng Zhang, Xiangyang Qi, Wei Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/10882907/
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author Chaoyue Liu
Yunkai Deng
Zhimin Zhang
Huaitao Fan
Heng Zhang
Xiangyang Qi
Wei Wang
author_facet Chaoyue Liu
Yunkai Deng
Zhimin Zhang
Huaitao Fan
Heng Zhang
Xiangyang Qi
Wei Wang
author_sort Chaoyue Liu
collection DOAJ
description Maritime ship detection is an essential prerequisite for targeting key objectives and safeguarding the security of territorial waters. The all-day and all-weather operational capability of synthetic aperture radar (SAR) makes SAR-based ship detection indispensable for maritime surveillance. Marine surveillance requires extensive coverage for large-scale searches. But there is a contradiction between high resolution and wide swath, which cannot be taken into account. Most existing marine surveillance modes generally exchange extensive coverage at the expense of spatial resolution. The 2-D detailed information is lost in this way, which is not conducive to target classification. Furthermore, real-time detection becomes a challenge under the constraints of limited on-board conditions. In this article, a novel marine surveillance mode is proposed. It divides the target search task into two parts: wide-area target detection in 2-D asymmetric resolution mode (2-D-ARM) and key target focusing in 2-D high-resolution mode. In the context of 2-D-ARM, the sparsity of the targets and the joint sparse low-rank characteristics of the background are studied, and a low-rank approximation model is developed to accomplish the task of real-time ship detection. The experiments show that the proposed method can realize the sparse target matrix extraction (STME) through matrix decomposition. Using Sentinel-1A, Japanese Advanced Land Observing Satellite (ALOS) PALSAR, and Gaofen3 single-polarization single-look complex data, the 2-D-ARM imaging is simulated, and a dataset is built to verify the processing performance of the proposed method.
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institution DOAJ
issn 1939-1404
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publishDate 2025-01-01
publisher IEEE
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series IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
spelling doaj-art-71fb8ac227174876a56952448733b9f62025-08-20T02:56:03ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-01187221723510.1109/JSTARS.2025.354090210882907TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution ModeChaoyue Liu0https://orcid.org/0009-0002-7279-7541Yunkai Deng1Zhimin Zhang2Huaitao Fan3https://orcid.org/0000-0002-8041-5358Heng Zhang4https://orcid.org/0000-0003-3635-5826Xiangyang Qi5Wei Wang6https://orcid.org/0000-0003-4251-3464Department of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaDepartment of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaDepartment of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaDepartment of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaDepartment of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaDepartment of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaDepartment of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaMaritime ship detection is an essential prerequisite for targeting key objectives and safeguarding the security of territorial waters. The all-day and all-weather operational capability of synthetic aperture radar (SAR) makes SAR-based ship detection indispensable for maritime surveillance. Marine surveillance requires extensive coverage for large-scale searches. But there is a contradiction between high resolution and wide swath, which cannot be taken into account. Most existing marine surveillance modes generally exchange extensive coverage at the expense of spatial resolution. The 2-D detailed information is lost in this way, which is not conducive to target classification. Furthermore, real-time detection becomes a challenge under the constraints of limited on-board conditions. In this article, a novel marine surveillance mode is proposed. It divides the target search task into two parts: wide-area target detection in 2-D asymmetric resolution mode (2-D-ARM) and key target focusing in 2-D high-resolution mode. In the context of 2-D-ARM, the sparsity of the targets and the joint sparse low-rank characteristics of the background are studied, and a low-rank approximation model is developed to accomplish the task of real-time ship detection. The experiments show that the proposed method can realize the sparse target matrix extraction (STME) through matrix decomposition. Using Sentinel-1A, Japanese Advanced Land Observing Satellite (ALOS) PALSAR, and Gaofen3 single-polarization single-look complex data, the 2-D-ARM imaging is simulated, and a dataset is built to verify the processing performance of the proposed method.https://ieeexplore.ieee.org/document/10882907/Low-rank approximationship detectionsparse target matrix extraction (STME)synthetic aperture radar (SAR)2-D asymmetric resolution mode (2-D-ARM)
spellingShingle Chaoyue Liu
Yunkai Deng
Zhimin Zhang
Huaitao Fan
Heng Zhang
Xiangyang Qi
Wei Wang
TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Low-rank approximation
ship detection
sparse target matrix extraction (STME)
synthetic aperture radar (SAR)
2-D asymmetric resolution mode (2-D-ARM)
title TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode
title_full TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode
title_fullStr TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode
title_full_unstemmed TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode
title_short TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode
title_sort tnn stme a matrix decomposition method for sar ship real time detection using 2 d asymmetric resolution mode
topic Low-rank approximation
ship detection
sparse target matrix extraction (STME)
synthetic aperture radar (SAR)
2-D asymmetric resolution mode (2-D-ARM)
url https://ieeexplore.ieee.org/document/10882907/
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