Shengqi Liu, Ronghui Zhan, Wang Wei, Qinglin Zhai, Zhang Jun
{"title":"基于联合稀疏表示的全极化HRRP识别","authors":"Shengqi Liu, Ronghui Zhan, Wang Wei, Qinglin Zhai, Zhang Jun","doi":"10.1109/RADARCONF.2015.7411903","DOIUrl":null,"url":null,"abstract":"Full-polarization high range resolution profile (FPHRRP) contains rich information regarding the signatures of a target which can be extracted for target recognition. The four polarization combinations data are correlated for they characterize the same target from a specific aspect angle using different polarization modes. To efficiently utilize the information for recognition performance enhancement, a joint sparse representation (JSR) based method for FPHRRP recognition is presented. Each single-polarization HRRP is represented by the atoms which are adaptively selected from its corresponding dictionary, and these atoms derived from different dictionaries have the same index set. Compared to conventional methods, the proposed method has the significant advantage of exploiting the correlation among single-polarization HRRPs to boost recognition performance. The experiment results show that the proposed method achieves promising recognition accuracy and is robust with respect to noisy observations.","PeriodicalId":267194,"journal":{"name":"2015 IEEE Radar Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Full-polarization HRRP recognition based on joint sparse representation\",\"authors\":\"Shengqi Liu, Ronghui Zhan, Wang Wei, Qinglin Zhai, Zhang Jun\",\"doi\":\"10.1109/RADARCONF.2015.7411903\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Full-polarization high range resolution profile (FPHRRP) contains rich information regarding the signatures of a target which can be extracted for target recognition. The four polarization combinations data are correlated for they characterize the same target from a specific aspect angle using different polarization modes. To efficiently utilize the information for recognition performance enhancement, a joint sparse representation (JSR) based method for FPHRRP recognition is presented. Each single-polarization HRRP is represented by the atoms which are adaptively selected from its corresponding dictionary, and these atoms derived from different dictionaries have the same index set. Compared to conventional methods, the proposed method has the significant advantage of exploiting the correlation among single-polarization HRRPs to boost recognition performance. The experiment results show that the proposed method achieves promising recognition accuracy and is robust with respect to noisy observations.\",\"PeriodicalId\":267194,\"journal\":{\"name\":\"2015 IEEE Radar Conference\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Radar Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADARCONF.2015.7411903\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Radar Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADARCONF.2015.7411903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Full-polarization HRRP recognition based on joint sparse representation
Full-polarization high range resolution profile (FPHRRP) contains rich information regarding the signatures of a target which can be extracted for target recognition. The four polarization combinations data are correlated for they characterize the same target from a specific aspect angle using different polarization modes. To efficiently utilize the information for recognition performance enhancement, a joint sparse representation (JSR) based method for FPHRRP recognition is presented. Each single-polarization HRRP is represented by the atoms which are adaptively selected from its corresponding dictionary, and these atoms derived from different dictionaries have the same index set. Compared to conventional methods, the proposed method has the significant advantage of exploiting the correlation among single-polarization HRRPs to boost recognition performance. The experiment results show that the proposed method achieves promising recognition accuracy and is robust with respect to noisy observations.