{"title":"ATR SAR数据的信息评估","authors":"Erik Blasch, M. Bryant","doi":"10.1109/NAECON.1998.710144","DOIUrl":null,"url":null,"abstract":"Without successful adaptive multisensor fusion or online registration techniques, automatic target recognition (ATR) algorithms are prone to poor object classifications. Multisensor fusion for a given situation assessment includes identifying measurement information for task completion and reducing image uncertainty in the presence of clutter. By extracting synthetic aperture radar (SAR) image informational features, image registration and target classification is achievable. This paper examines SAR information-theoretic features for a target orientation and proposes a method for target classification.","PeriodicalId":202280,"journal":{"name":"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)","volume":"417 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Information assessment of SAR data for ATR\",\"authors\":\"Erik Blasch, M. Bryant\",\"doi\":\"10.1109/NAECON.1998.710144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Without successful adaptive multisensor fusion or online registration techniques, automatic target recognition (ATR) algorithms are prone to poor object classifications. Multisensor fusion for a given situation assessment includes identifying measurement information for task completion and reducing image uncertainty in the presence of clutter. By extracting synthetic aperture radar (SAR) image informational features, image registration and target classification is achievable. This paper examines SAR information-theoretic features for a target orientation and proposes a method for target classification.\",\"PeriodicalId\":202280,\"journal\":{\"name\":\"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)\",\"volume\":\"417 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAECON.1998.710144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON.1998.710144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Without successful adaptive multisensor fusion or online registration techniques, automatic target recognition (ATR) algorithms are prone to poor object classifications. Multisensor fusion for a given situation assessment includes identifying measurement information for task completion and reducing image uncertainty in the presence of clutter. By extracting synthetic aperture radar (SAR) image informational features, image registration and target classification is achievable. This paper examines SAR information-theoretic features for a target orientation and proposes a method for target classification.