{"title":"A fast time-delay estimator for linear frequency modulation signal based on frFt","authors":"Cui Yang, Yue Yu, Chaonan Wu, Geng-xin Ning","doi":"10.1109/ITNEC.2019.8729240","DOIUrl":null,"url":null,"abstract":"A fast time-delay estimator for linear frequency modulation signal is proposed. The new estimator, named by frFt-TELS, searches the maximal bin of fractional Fourier transform (frFt) as a coarse estimation. Then Taylor expansion of theoretical frFt power spectrum around the coarse estimation is deduced. Least squares approximation between the theoretical frFt power spectrum and the frFt power spectrum of the given sample data is applied to get the fine estimation. Simulations demonstrated that frFt-TELS approaches the performance of traditional estimator with less computational complexity.","PeriodicalId":202966,"journal":{"name":"2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNEC.2019.8729240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A fast time-delay estimator for linear frequency modulation signal is proposed. The new estimator, named by frFt-TELS, searches the maximal bin of fractional Fourier transform (frFt) as a coarse estimation. Then Taylor expansion of theoretical frFt power spectrum around the coarse estimation is deduced. Least squares approximation between the theoretical frFt power spectrum and the frFt power spectrum of the given sample data is applied to get the fine estimation. Simulations demonstrated that frFt-TELS approaches the performance of traditional estimator with less computational complexity.