{"title":"A technique for estimating the parameters of multiple polynomial phase signals","authors":"S. Peleg, B. Friedlander","doi":"10.1109/TFTSA.1992.274221","DOIUrl":null,"url":null,"abstract":"An iterative algorithm for estimating the parameters of multiple superimposed polynomial phase signals is presented. The algorithm is based on the ability of the discrete polynomial transform (DPT) to estimate the parameters of a polynomial phase signal in the presence of other interfering signals. The parameters of one of the signals having been estimated, it can be filtered out from the composite signal. The procedure is then applied to the remainder, which contains a smaller number of components. In extensive testing it was found that the algorithm works very well in general. It is able to reliably separate multiple signals and to accurately estimate their parameters.<<ETX>>","PeriodicalId":105228,"journal":{"name":"[1992] Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TFTSA.1992.274221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
An iterative algorithm for estimating the parameters of multiple superimposed polynomial phase signals is presented. The algorithm is based on the ability of the discrete polynomial transform (DPT) to estimate the parameters of a polynomial phase signal in the presence of other interfering signals. The parameters of one of the signals having been estimated, it can be filtered out from the composite signal. The procedure is then applied to the remainder, which contains a smaller number of components. In extensive testing it was found that the algorithm works very well in general. It is able to reliably separate multiple signals and to accurately estimate their parameters.<>