{"title":"Time Delay Estimation Based on the Fractional Fourier Transform in the Passive System","authors":"Xue Mei Li, R. Tao, Yue Wang","doi":"10.1109/CISP.2009.5302590","DOIUrl":null,"url":null,"abstract":"The time delay estimation between two signals in the passive system has been an important issue. In this paper, we propose a new time delay estimator based on the delay property of the fractional Fourier transform (FRFT). It is suitable for chirp signals in the passive system. The time delay is evaluated in the fractional Fourier domain by measuring the time differential between the time delays obtained from the two peak values of the fractional spectra of the received signals. Simulation results show that the proposed time delay method performs better than the conventional cross correlation approach at low signal-to-noise (SNR).","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5302590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The time delay estimation between two signals in the passive system has been an important issue. In this paper, we propose a new time delay estimator based on the delay property of the fractional Fourier transform (FRFT). It is suitable for chirp signals in the passive system. The time delay is evaluated in the fractional Fourier domain by measuring the time differential between the time delays obtained from the two peak values of the fractional spectra of the received signals. Simulation results show that the proposed time delay method performs better than the conventional cross correlation approach at low signal-to-noise (SNR).