{"title":"相关Pareto分布海杂波仿真","authors":"S. Bocquet","doi":"10.1109/RADAR.2013.6651995","DOIUrl":null,"url":null,"abstract":"The memoryless nonlinear transformation method is used to simulate Pareto distributed sea clutter with a specified correlation function for the clutter power. The Pareto distribution is formed from a compound model with a negative exponential distribution for the speckle intensity and an inverse gamma distribution for the clutter power. An estimator based on the expectation value of z log z is obtained for the Pareto shape parameter, which has comparable accuracy to the maximum likelihood estimator and the advantage of also being applicable to the compound gamma distribution which arises for multiple looks.","PeriodicalId":365285,"journal":{"name":"2013 International Conference on Radar","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Simulation of correlated Pareto distributed sea clutter\",\"authors\":\"S. Bocquet\",\"doi\":\"10.1109/RADAR.2013.6651995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The memoryless nonlinear transformation method is used to simulate Pareto distributed sea clutter with a specified correlation function for the clutter power. The Pareto distribution is formed from a compound model with a negative exponential distribution for the speckle intensity and an inverse gamma distribution for the clutter power. An estimator based on the expectation value of z log z is obtained for the Pareto shape parameter, which has comparable accuracy to the maximum likelihood estimator and the advantage of also being applicable to the compound gamma distribution which arises for multiple looks.\",\"PeriodicalId\":365285,\"journal\":{\"name\":\"2013 International Conference on Radar\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Radar\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2013.6651995\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Radar","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2013.6651995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulation of correlated Pareto distributed sea clutter
The memoryless nonlinear transformation method is used to simulate Pareto distributed sea clutter with a specified correlation function for the clutter power. The Pareto distribution is formed from a compound model with a negative exponential distribution for the speckle intensity and an inverse gamma distribution for the clutter power. An estimator based on the expectation value of z log z is obtained for the Pareto shape parameter, which has comparable accuracy to the maximum likelihood estimator and the advantage of also being applicable to the compound gamma distribution which arises for multiple looks.
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