A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation
Abstract Linear frequency modulation (LFM) signal is a common radar signal in modern electronic warfare, and smeared spectrum (SMSP) can generate multiple false targets, causing jamming to radar detection. The authors propose a chirplet‐based masking algorithm that can solve the problem of SMSP jamm...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-09-01
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| Series: | IET Radar, Sonar & Navigation |
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| Online Access: | https://doi.org/10.1049/rsn2.12587 |
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| author | Yifan Wang Yibing Li Gang Yu Xiaoyu Geng Zitao Zhou |
| author_facet | Yifan Wang Yibing Li Gang Yu Xiaoyu Geng Zitao Zhou |
| author_sort | Yifan Wang |
| collection | DOAJ |
| description | Abstract Linear frequency modulation (LFM) signal is a common radar signal in modern electronic warfare, and smeared spectrum (SMSP) can generate multiple false targets, causing jamming to radar detection. The authors propose a chirplet‐based masking algorithm that can solve the problem of SMSP jamming suppression and address a more complex problem: the separation of jamming signal and multiple LFM signals from intercepted mixed signal. First, the authors obtain matched chirp rates of the source signals through the changing tendency of the Rényi entropy. Then, the ridge of each source signal is extracted from the high‐resolution chirplet transform result using an image processing‐based algorithm. Finally, the jamming and LFM signals are accurately reconstructed through the time‐frequency mask to achieve separation. Even in the extreme case where multiple source signals with close chirp rates are overlapped, the proposed slope‐matching ridge extraction method and iterative update reconstruction method can still achieve commendable signal separation effects. Extensive experimental results demonstrate that the proposed algorithm performs well under extreme conditions of low signal‐to‐noise ratio, high jamming‐to‐signal ratio, and high sea state. |
| format | Article |
| id | doaj-art-5063df94a7f04c1da96039f3f83e3960 |
| institution | Kabale University |
| issn | 1751-8784 1751-8792 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Radar, Sonar & Navigation |
| spelling | doaj-art-5063df94a7f04c1da96039f3f83e39602024-11-17T12:04:35ZengWileyIET Radar, Sonar & Navigation1751-87841751-87922024-09-011891409143010.1049/rsn2.12587A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separationYifan Wang0Yibing Li1Gang Yu2Xiaoyu Geng3Zitao Zhou4College of Information and Communication Engineering Harbin Engineering University Harbin ChinaCollege of Information and Communication Engineering Harbin Engineering University Harbin ChinaSchool of Electrical Engineering University of Jinan Jinan ChinaCollege of Information and Communication Engineering Harbin Engineering University Harbin ChinaCollege of Information and Communication Engineering Harbin Engineering University Harbin ChinaAbstract Linear frequency modulation (LFM) signal is a common radar signal in modern electronic warfare, and smeared spectrum (SMSP) can generate multiple false targets, causing jamming to radar detection. The authors propose a chirplet‐based masking algorithm that can solve the problem of SMSP jamming suppression and address a more complex problem: the separation of jamming signal and multiple LFM signals from intercepted mixed signal. First, the authors obtain matched chirp rates of the source signals through the changing tendency of the Rényi entropy. Then, the ridge of each source signal is extracted from the high‐resolution chirplet transform result using an image processing‐based algorithm. Finally, the jamming and LFM signals are accurately reconstructed through the time‐frequency mask to achieve separation. Even in the extreme case where multiple source signals with close chirp rates are overlapped, the proposed slope‐matching ridge extraction method and iterative update reconstruction method can still achieve commendable signal separation effects. Extensive experimental results demonstrate that the proposed algorithm performs well under extreme conditions of low signal‐to‐noise ratio, high jamming‐to‐signal ratio, and high sea state.https://doi.org/10.1049/rsn2.12587blind source separationinterference suppressiontime‐frequency analysis |
| spellingShingle | Yifan Wang Yibing Li Gang Yu Xiaoyu Geng Zitao Zhou A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation IET Radar, Sonar & Navigation blind source separation interference suppression time‐frequency analysis |
| title | A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation |
| title_full | A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation |
| title_fullStr | A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation |
| title_full_unstemmed | A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation |
| title_short | A chirplet‐based masking algorithm for smeared spectrum jamming suppression and signal separation |
| title_sort | chirplet based masking algorithm for smeared spectrum jamming suppression and signal separation |
| topic | blind source separation interference suppression time‐frequency analysis |
| url | https://doi.org/10.1049/rsn2.12587 |
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