{"title":"多视点电磁想象","authors":"Dan Xu, Guangcai Sun, M. Xing","doi":"10.1109/COMPEM.2018.8496670","DOIUrl":null,"url":null,"abstract":"The traditional multi-view imaging approach is based on image processing. However, it suffers from the difficult interpretation and poor visibility of the synthetic aperture radar(SAR) images when the weaker scattering components are masked by the nearby stronger scattering components. To overcome the drawback, a multi-view electromagnetic imaging based on attributed scattering center model is introduced. Firstly, the full aperture is divided into several overlay sub views to estimate each component's parameters. Then all components are rotated to the same view and the component's parameters information fusion is carried out. Finally, several compare experiments are provided to verify the effectiveness of the proposed algorithm.","PeriodicalId":221352,"journal":{"name":"2018 IEEE International Conference on Computational Electromagnetics (ICCEM)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi-View Electromagnetic Imagining\",\"authors\":\"Dan Xu, Guangcai Sun, M. Xing\",\"doi\":\"10.1109/COMPEM.2018.8496670\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The traditional multi-view imaging approach is based on image processing. However, it suffers from the difficult interpretation and poor visibility of the synthetic aperture radar(SAR) images when the weaker scattering components are masked by the nearby stronger scattering components. To overcome the drawback, a multi-view electromagnetic imaging based on attributed scattering center model is introduced. Firstly, the full aperture is divided into several overlay sub views to estimate each component's parameters. Then all components are rotated to the same view and the component's parameters information fusion is carried out. Finally, several compare experiments are provided to verify the effectiveness of the proposed algorithm.\",\"PeriodicalId\":221352,\"journal\":{\"name\":\"2018 IEEE International Conference on Computational Electromagnetics (ICCEM)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Computational Electromagnetics (ICCEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPEM.2018.8496670\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Computational Electromagnetics (ICCEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPEM.2018.8496670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The traditional multi-view imaging approach is based on image processing. However, it suffers from the difficult interpretation and poor visibility of the synthetic aperture radar(SAR) images when the weaker scattering components are masked by the nearby stronger scattering components. To overcome the drawback, a multi-view electromagnetic imaging based on attributed scattering center model is introduced. Firstly, the full aperture is divided into several overlay sub views to estimate each component's parameters. Then all components are rotated to the same view and the component's parameters information fusion is carried out. Finally, several compare experiments are provided to verify the effectiveness of the proposed algorithm.
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