{"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}
引用次数: 3
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.