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Hierarchical Jamming Recognition with Spectrum Fusion Feature and Twin-bound SVM for Cognitive Satellite Communications
In satellite communications, signals are vulnerable to radio frequency jamming, especially in aerospace tracking telemetry and command (TT&C) systems and global navigation satellite system (GNSS). It is quite essential to jamming suppression for unknown jamming signals to ensure the safety of co...
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creator | Wei, Yi Ou-Yang, Shang-Rong Li, Chao Liu, Qi Qian, Yu-Bi |
description | In satellite communications, signals are vulnerable to radio frequency jamming, especially in aerospace tracking telemetry and command (TT&C) systems and global navigation satellite system (GNSS). It is quite essential to jamming suppression for unknown jamming signals to ensure the safety of communication links, and the design of the jamming type recognition algorithm is a basic prerequisite of effectively anti-jamming, especially for the cognitive satellite communications. In this work, considering the limited resource of satellites, a fast jamming recognition algorithm is proposed to detect and classify the jamming signals with low time complexity in the process of data transmission. By taking advantage of the spectrum fusion feature and making full use of the anti-jamming prior information, the proposed algorithm combines the idea of the twin support vector machine (SVM) and the solution-oriented hierarchical classification to reduce the online time complexity with high recognition accuracy. Simulation results demonstrate the clear superiority of the proposed algorithm vis-à-vis other baseline competitors. |
doi_str_mv | 10.1109/WCNC55385.2023.10119124 |
format | conference_proceeding |
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It is quite essential to jamming suppression for unknown jamming signals to ensure the safety of communication links, and the design of the jamming type recognition algorithm is a basic prerequisite of effectively anti-jamming, especially for the cognitive satellite communications. In this work, considering the limited resource of satellites, a fast jamming recognition algorithm is proposed to detect and classify the jamming signals with low time complexity in the process of data transmission. By taking advantage of the spectrum fusion feature and making full use of the anti-jamming prior information, the proposed algorithm combines the idea of the twin support vector machine (SVM) and the solution-oriented hierarchical classification to reduce the online time complexity with high recognition accuracy. 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Simulation results demonstrate the clear superiority of the proposed algorithm vis-à-vis other baseline competitors.</description><subject>and spectrum sensing</subject><subject>Classification algorithms</subject><subject>cognitive satellite communication</subject><subject>Global navigation satellite system</subject><subject>hierarchical classification</subject><subject>Jamming recognition</subject><subject>machine learning</subject><subject>Satellite broadcasting</subject><subject>Satellites</subject><subject>Sensors</subject><subject>Simulation</subject><subject>Support vector machines</subject><subject>twin-bound support vector machine (SVM)</subject><issn>1558-2612</issn><isbn>9781665491228</isbn><isbn>1665491221</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1UF1Lw0AQPAXBWvsPBO8PpN5u7i7JowRrlapgqz6Wy2XTnuSjJJcW_70p1afdmWFmmWXsFsQUQCR3X-lrqlQYqykKDKcgABJAecYmSRSD1koOEONzNgKl4gA14CW76rpvIVAoKUfsMHfUmtZunTUlfzZV5eoNfyfbbGrnXVPzg_NbvtyR9W1f8VnfHckZGd-3xE2d89XB1UHW9MO6_HzhRdPy9OTeE18aT2XpPA1cVfX1cOaY2l2zi8KUHU3-5ph9zB5W6TxYvD0-pfeLwKGQPsAszzGKUAodKUyixEZZRkKH2hRkM13kMCg2z5QEY0koDTRUBYwRrUQKx-zmlOuIaL1rXWXan_X_o8JftAhfHA</recordid><startdate>202303</startdate><enddate>202303</enddate><creator>Wei, Yi</creator><creator>Ou-Yang, Shang-Rong</creator><creator>Li, Chao</creator><creator>Liu, Qi</creator><creator>Qian, Yu-Bi</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>202303</creationdate><title>Hierarchical Jamming Recognition with Spectrum Fusion Feature and Twin-bound SVM for Cognitive Satellite Communications</title><author>Wei, Yi ; Ou-Yang, Shang-Rong ; Li, Chao ; Liu, Qi ; Qian, Yu-Bi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i204t-2bdd2772406752979c7bbe0636afecb6fd1067cdb541ace0561e15512822c42e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>and spectrum sensing</topic><topic>Classification algorithms</topic><topic>cognitive satellite communication</topic><topic>Global navigation satellite system</topic><topic>hierarchical classification</topic><topic>Jamming recognition</topic><topic>machine learning</topic><topic>Satellite broadcasting</topic><topic>Satellites</topic><topic>Sensors</topic><topic>Simulation</topic><topic>Support vector machines</topic><topic>twin-bound support vector machine (SVM)</topic><toplevel>online_resources</toplevel><creatorcontrib>Wei, Yi</creatorcontrib><creatorcontrib>Ou-Yang, Shang-Rong</creatorcontrib><creatorcontrib>Li, Chao</creatorcontrib><creatorcontrib>Liu, Qi</creatorcontrib><creatorcontrib>Qian, Yu-Bi</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wei, Yi</au><au>Ou-Yang, Shang-Rong</au><au>Li, Chao</au><au>Liu, Qi</au><au>Qian, Yu-Bi</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Hierarchical Jamming Recognition with Spectrum Fusion Feature and Twin-bound SVM for Cognitive Satellite Communications</atitle><btitle>2023 IEEE Wireless Communications and Networking Conference (WCNC)</btitle><stitle>WCNC</stitle><date>2023-03</date><risdate>2023</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><eissn>1558-2612</eissn><eisbn>9781665491228</eisbn><eisbn>1665491221</eisbn><abstract>In satellite communications, signals are vulnerable to radio frequency jamming, especially in aerospace tracking telemetry and command (TT&C) systems and global navigation satellite system (GNSS). It is quite essential to jamming suppression for unknown jamming signals to ensure the safety of communication links, and the design of the jamming type recognition algorithm is a basic prerequisite of effectively anti-jamming, especially for the cognitive satellite communications. In this work, considering the limited resource of satellites, a fast jamming recognition algorithm is proposed to detect and classify the jamming signals with low time complexity in the process of data transmission. By taking advantage of the spectrum fusion feature and making full use of the anti-jamming prior information, the proposed algorithm combines the idea of the twin support vector machine (SVM) and the solution-oriented hierarchical classification to reduce the online time complexity with high recognition accuracy. 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subjects | and spectrum sensing Classification algorithms cognitive satellite communication Global navigation satellite system hierarchical classification Jamming recognition machine learning Satellite broadcasting Satellites Sensors Simulation Support vector machines twin-bound support vector machine (SVM) |
title | Hierarchical Jamming Recognition with Spectrum Fusion Feature and Twin-bound SVM for Cognitive Satellite Communications |
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