{"title":"利用偏振层析SAR数据进行建筑物表征","authors":"S. Guillaso, O. D’Hondt, O. Hellwich","doi":"10.1109/JURSE.2013.6550708","DOIUrl":null,"url":null,"abstract":"This paper describes the characterization of buildings using fully polarimetric tomographic SAR data at L-Band. This analysis is performed in three steps. Polarimetric tomographic data are first processed using the high resolution spectral estimator MUSIC (FP-MUSIC-1), assuming 1 scatterer. Then, points of interest are extracted using a novel signal-to-noise index. A strong reduction of artifacts is observed. Finally, detected scatterers are identified by retrieving their polarization state.","PeriodicalId":370707,"journal":{"name":"Joint Urban Remote Sensing Event 2013","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Building characterization using polarimetric tomographic SAR data\",\"authors\":\"S. Guillaso, O. D’Hondt, O. Hellwich\",\"doi\":\"10.1109/JURSE.2013.6550708\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the characterization of buildings using fully polarimetric tomographic SAR data at L-Band. This analysis is performed in three steps. Polarimetric tomographic data are first processed using the high resolution spectral estimator MUSIC (FP-MUSIC-1), assuming 1 scatterer. Then, points of interest are extracted using a novel signal-to-noise index. A strong reduction of artifacts is observed. Finally, detected scatterers are identified by retrieving their polarization state.\",\"PeriodicalId\":370707,\"journal\":{\"name\":\"Joint Urban Remote Sensing Event 2013\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Joint Urban Remote Sensing Event 2013\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/JURSE.2013.6550708\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Joint Urban Remote Sensing Event 2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JURSE.2013.6550708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Building characterization using polarimetric tomographic SAR data
This paper describes the characterization of buildings using fully polarimetric tomographic SAR data at L-Band. This analysis is performed in three steps. Polarimetric tomographic data are first processed using the high resolution spectral estimator MUSIC (FP-MUSIC-1), assuming 1 scatterer. Then, points of interest are extracted using a novel signal-to-noise index. A strong reduction of artifacts is observed. Finally, detected scatterers are identified by retrieving their polarization state.