W. Zhang, Kai Zeng, Chuan Zhu, Xingyue Long, Wei Yi
{"title":"雷达系统弱目标多帧联合跟踪与分类方法","authors":"W. Zhang, Kai Zeng, Chuan Zhu, Xingyue Long, Wei Yi","doi":"10.1109/ICCAIS56082.2022.9990283","DOIUrl":null,"url":null,"abstract":"This paper solves the problem of joint tracking and classification of weak targets using multi-frame joint processing technology. Weak targets are easily submerged in background noise, and single-frame threshold detection makes many of their feature information lost, making it challenging to track and classify them effectively. Aiming at solving these problems, a multi-frame joint tracking and classification (MF-JTC) method is proposed. The method achieves the accurate estimation of the motion trajectory and target class by jointly processing the radar measurement data in multi-frames. Finally, the results show that compared with the traditional single-frame joint tracking and classification (SF-JTC) method, the proposed method has better tracking and classification performance for weak targets.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Multi-Frame Joint Tracking and Classification Method for Weak Target in Radar System\",\"authors\":\"W. Zhang, Kai Zeng, Chuan Zhu, Xingyue Long, Wei Yi\",\"doi\":\"10.1109/ICCAIS56082.2022.9990283\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper solves the problem of joint tracking and classification of weak targets using multi-frame joint processing technology. Weak targets are easily submerged in background noise, and single-frame threshold detection makes many of their feature information lost, making it challenging to track and classify them effectively. Aiming at solving these problems, a multi-frame joint tracking and classification (MF-JTC) method is proposed. The method achieves the accurate estimation of the motion trajectory and target class by jointly processing the radar measurement data in multi-frames. Finally, the results show that compared with the traditional single-frame joint tracking and classification (SF-JTC) method, the proposed method has better tracking and classification performance for weak targets.\",\"PeriodicalId\":273404,\"journal\":{\"name\":\"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCAIS56082.2022.9990283\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAIS56082.2022.9990283","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-Frame Joint Tracking and Classification Method for Weak Target in Radar System
This paper solves the problem of joint tracking and classification of weak targets using multi-frame joint processing technology. Weak targets are easily submerged in background noise, and single-frame threshold detection makes many of their feature information lost, making it challenging to track and classify them effectively. Aiming at solving these problems, a multi-frame joint tracking and classification (MF-JTC) method is proposed. The method achieves the accurate estimation of the motion trajectory and target class by jointly processing the radar measurement data in multi-frames. Finally, the results show that compared with the traditional single-frame joint tracking and classification (SF-JTC) method, the proposed method has better tracking and classification performance for weak targets.