{"title":"全距离TMA性能","authors":"Annie-Claude Pérez, C. Jauffret, D. Pillon","doi":"10.1109/CAMSAP.2017.8313076","DOIUrl":null,"url":null,"abstract":"Range-only target motion analysis (ROTMA) is the topic of this paper: we focus our study on the numerical aspect and performance of the maximum likelihood estimates (MLE) for some scenarios when the noise polluting the measurements is additive and Gaussian. The performance is compared to the Cramér-Rao lower bound (CRLB).","PeriodicalId":315977,"journal":{"name":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Performance of range-only TMA\",\"authors\":\"Annie-Claude Pérez, C. Jauffret, D. Pillon\",\"doi\":\"10.1109/CAMSAP.2017.8313076\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Range-only target motion analysis (ROTMA) is the topic of this paper: we focus our study on the numerical aspect and performance of the maximum likelihood estimates (MLE) for some scenarios when the noise polluting the measurements is additive and Gaussian. The performance is compared to the Cramér-Rao lower bound (CRLB).\",\"PeriodicalId\":315977,\"journal\":{\"name\":\"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMSAP.2017.8313076\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMSAP.2017.8313076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Range-only target motion analysis (ROTMA) is the topic of this paper: we focus our study on the numerical aspect and performance of the maximum likelihood estimates (MLE) for some scenarios when the noise polluting the measurements is additive and Gaussian. The performance is compared to the Cramér-Rao lower bound (CRLB).