{"title":"基于极值理论的分布无关CFAR探测器","authors":"M. Piotrkowski","doi":"10.1109/IRS.2006.4338005","DOIUrl":null,"url":null,"abstract":"According to the extreme value theory, the tail distribution of virtually any statistical distribution can be uniquely modeled by the generalized Pareto distribution. Based on this property, a CFAR detector making no assumption about the distribution of interference is proposed. The parameters of the generalized Pareto distribution can be estimated using the method of L-moments. The performance of the new detector is compared to CA- and Optimized Weibull CFAR detector in the Rayleigh, Weibull and lognormally distributed clutter amplitude.","PeriodicalId":124475,"journal":{"name":"2006 International Radar Symposium","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Distribution Independent CFAR Detector Using Extreme Value Theory\",\"authors\":\"M. Piotrkowski\",\"doi\":\"10.1109/IRS.2006.4338005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to the extreme value theory, the tail distribution of virtually any statistical distribution can be uniquely modeled by the generalized Pareto distribution. Based on this property, a CFAR detector making no assumption about the distribution of interference is proposed. The parameters of the generalized Pareto distribution can be estimated using the method of L-moments. The performance of the new detector is compared to CA- and Optimized Weibull CFAR detector in the Rayleigh, Weibull and lognormally distributed clutter amplitude.\",\"PeriodicalId\":124475,\"journal\":{\"name\":\"2006 International Radar Symposium\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Radar Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRS.2006.4338005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Radar Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRS.2006.4338005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distribution Independent CFAR Detector Using Extreme Value Theory
According to the extreme value theory, the tail distribution of virtually any statistical distribution can be uniquely modeled by the generalized Pareto distribution. Based on this property, a CFAR detector making no assumption about the distribution of interference is proposed. The parameters of the generalized Pareto distribution can be estimated using the method of L-moments. The performance of the new detector is compared to CA- and Optimized Weibull CFAR detector in the Rayleigh, Weibull and lognormally distributed clutter amplitude.
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