Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods
Passive radar plays an important role in early warning detection and Low Slow Small (LSS) target detection. Due to the uncontrollable source of passive radar signal radiations, target characteristics are more complex, which makes target detection and identification extremely difficult. In this paper...
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China Science Publishing & Media Ltd. (CSPM)
2025-04-01
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| Series: | Leida xuebao |
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| Online Access: | https://radars.ac.cn/cn/article/doi/10.12000/JR24145 |
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| author | Xiaolong CHEN Guilin RAO Jian GUAN Jinhao WANG Hongyong WANG Caisheng ZHANG Jianxin YI Xianrong WAN Yunhua RAO |
| author_facet | Xiaolong CHEN Guilin RAO Jian GUAN Jinhao WANG Hongyong WANG Caisheng ZHANG Jianxin YI Xianrong WAN Yunhua RAO |
| author_sort | Xiaolong CHEN |
| collection | DOAJ |
| description | Passive radar plays an important role in early warning detection and Low Slow Small (LSS) target detection. Due to the uncontrollable source of passive radar signal radiations, target characteristics are more complex, which makes target detection and identification extremely difficult. In this paper, a passive radar LSS detection dataset (LSS-PR-1.0) is constructed, which contains the radar echo signals of four typical sea and air targets, namely helicopters, unmanned aerial vehicles, speedboats, and passenger ships, as well as sea clutter data at low and high sea states. It provides data support for radar research. In terms of target feature extraction and analysis, the singular-value-decomposition sea-clutter-suppression method is first adopted to remove the influence of the strong Bragg peak of sea clutter on target echo. On this basis, four categories of ten multi-domain feature extraction and analysis methods are proposed, including time-domain features (relative average amplitude), frequency-domain features (spectral features, Doppler waterfall plot, and range Doppler features), time-frequency-domain features, and motion features (heading difference, trajectory parameters, speed variation interval, speed variation coefficient, and acceleration). Based on the actual measurement data, a comparative analysis is conducted on the characteristics of four types of sea and air targets, summarizing the patterns of various target characteristics and laying the foundation for subsequent target recognition. |
| format | Article |
| id | doaj-art-4761a8ccb94d44f6bdb78a42891bde97 |
| institution | OA Journals |
| issn | 2095-283X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj-art-4761a8ccb94d44f6bdb78a42891bde972025-08-20T01:50:30ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2025-04-0114224926810.12000/JR24145R24145Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis MethodsXiaolong CHEN0Guilin RAO1Jian GUAN2Jinhao WANG3Hongyong WANG4Caisheng ZHANG5Jianxin YI6Xianrong WAN7Yunhua RAO8Naval Aviation University, Yantai 264001, ChinaNaval Aviation University, Yantai 264001, ChinaNaval Aviation University, Yantai 264001, ChinaNaval Aviation University, Yantai 264001, ChinaNaval Aviation University, Yantai 264001, ChinaNaval Aviation University, Yantai 264001, ChinaSchool of Electronic Information, Wuhan University, Wuhan 430072, ChinaSchool of Electronic Information, Wuhan University, Wuhan 430072, ChinaSchool of Electronic Information, Wuhan University, Wuhan 430072, ChinaPassive radar plays an important role in early warning detection and Low Slow Small (LSS) target detection. Due to the uncontrollable source of passive radar signal radiations, target characteristics are more complex, which makes target detection and identification extremely difficult. In this paper, a passive radar LSS detection dataset (LSS-PR-1.0) is constructed, which contains the radar echo signals of four typical sea and air targets, namely helicopters, unmanned aerial vehicles, speedboats, and passenger ships, as well as sea clutter data at low and high sea states. It provides data support for radar research. In terms of target feature extraction and analysis, the singular-value-decomposition sea-clutter-suppression method is first adopted to remove the influence of the strong Bragg peak of sea clutter on target echo. On this basis, four categories of ten multi-domain feature extraction and analysis methods are proposed, including time-domain features (relative average amplitude), frequency-domain features (spectral features, Doppler waterfall plot, and range Doppler features), time-frequency-domain features, and motion features (heading difference, trajectory parameters, speed variation interval, speed variation coefficient, and acceleration). Based on the actual measurement data, a comparative analysis is conducted on the characteristics of four types of sea and air targets, summarizing the patterns of various target characteristics and laying the foundation for subsequent target recognition.https://radars.ac.cn/cn/article/doi/10.12000/JR24145low slow small (lss) targetspassive radarsea clutter suppressionmulti-domain feature extractioncharacterizationpublicly available datasets |
| spellingShingle | Xiaolong CHEN Guilin RAO Jian GUAN Jinhao WANG Hongyong WANG Caisheng ZHANG Jianxin YI Xianrong WAN Yunhua RAO Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods Leida xuebao low slow small (lss) targets passive radar sea clutter suppression multi-domain feature extraction characterization publicly available datasets |
| title | Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods |
| title_full | Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods |
| title_fullStr | Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods |
| title_full_unstemmed | Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods |
| title_short | Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods |
| title_sort | passive radar low slow small detection dataset lss pr 1 0 and multi domain feature extraction and analysis methods |
| topic | low slow small (lss) targets passive radar sea clutter suppression multi-domain feature extraction characterization publicly available datasets |
| url | https://radars.ac.cn/cn/article/doi/10.12000/JR24145 |
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