{"title":"气象雷达极化分类的多元耦合方法","authors":"F. Yanovsky, A. Rudiakova, R. Sinitsyn","doi":"10.1109/IRS.2016.7497371","DOIUrl":null,"url":null,"abstract":"The paper presents a multivariate copula approach to identify the dependence between different polarimetric parameters. This approach can be used to develop a new method of invariant polarimetric classification of radar targets. Signals from meteorological target are processed as an example.","PeriodicalId":346680,"journal":{"name":"2016 17th International Radar Symposium (IRS)","volume":"25 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Multivariate copula approach for polarimetric classification in weather radar applications\",\"authors\":\"F. Yanovsky, A. Rudiakova, R. Sinitsyn\",\"doi\":\"10.1109/IRS.2016.7497371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a multivariate copula approach to identify the dependence between different polarimetric parameters. This approach can be used to develop a new method of invariant polarimetric classification of radar targets. Signals from meteorological target are processed as an example.\",\"PeriodicalId\":346680,\"journal\":{\"name\":\"2016 17th International Radar Symposium (IRS)\",\"volume\":\"25 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 17th International Radar Symposium (IRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRS.2016.7497371\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 17th International Radar Symposium (IRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRS.2016.7497371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multivariate copula approach for polarimetric classification in weather radar applications
The paper presents a multivariate copula approach to identify the dependence between different polarimetric parameters. This approach can be used to develop a new method of invariant polarimetric classification of radar targets. Signals from meteorological target are processed as an example.
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