{"title":"一种多目标ISAR成像新方法","authors":"Lei Liu, Feng Zhou, Yongqiang Guo, Mingliang Tao, Pange Sun, Zi-jing Zhang","doi":"10.1109/APSAR.2015.7306216","DOIUrl":null,"url":null,"abstract":"A novel multi-targets ISAR imaging method based on particle swarm optimization (PSO) and modified CLEAN technique is proposed in this paper. First, multi-targets are modeled as several separated group-targets in which translational motion of each target is analogous. And then, translational motion of each group-target is modeled as a polynomial, and the polynomial coefficient is estimated via PSO. Then focused image of the group-target can be obtained and extracted via a modified CLEAN technique. Meanwhile, each target can be segmented and extracted based on clustering number estimation and K-means clustering algorithm. Finally, better focused image of each target would be obtained through further traditional mono-target imaging processing. Experimental results verify the validity of the proposed method.","PeriodicalId":350698,"journal":{"name":"2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A novel method for multi-targets ISAR imaging\",\"authors\":\"Lei Liu, Feng Zhou, Yongqiang Guo, Mingliang Tao, Pange Sun, Zi-jing Zhang\",\"doi\":\"10.1109/APSAR.2015.7306216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel multi-targets ISAR imaging method based on particle swarm optimization (PSO) and modified CLEAN technique is proposed in this paper. First, multi-targets are modeled as several separated group-targets in which translational motion of each target is analogous. And then, translational motion of each group-target is modeled as a polynomial, and the polynomial coefficient is estimated via PSO. Then focused image of the group-target can be obtained and extracted via a modified CLEAN technique. Meanwhile, each target can be segmented and extracted based on clustering number estimation and K-means clustering algorithm. Finally, better focused image of each target would be obtained through further traditional mono-target imaging processing. Experimental results verify the validity of the proposed method.\",\"PeriodicalId\":350698,\"journal\":{\"name\":\"2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSAR.2015.7306216\",\"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 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSAR.2015.7306216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel multi-targets ISAR imaging method based on particle swarm optimization (PSO) and modified CLEAN technique is proposed in this paper. First, multi-targets are modeled as several separated group-targets in which translational motion of each target is analogous. And then, translational motion of each group-target is modeled as a polynomial, and the polynomial coefficient is estimated via PSO. Then focused image of the group-target can be obtained and extracted via a modified CLEAN technique. Meanwhile, each target can be segmented and extracted based on clustering number estimation and K-means clustering algorithm. Finally, better focused image of each target would be obtained through further traditional mono-target imaging processing. Experimental results verify the validity of the proposed method.