{"title":"Range-Doppler processing with the cone kernel time-frequency representation","authors":"J. Pitton, W. Fox, L. Atlas, J. Luby, P. Loughlin","doi":"10.1109/PACRIM.1991.160861","DOIUrl":null,"url":null,"abstract":"Range-Doppler processing is the primary tool in active sonar and radar imaging. The matched-filter is the optimal detector in sonar and radar, but has drawbacks in time and frequency resolution which may hinder its performance as a classifier. The authors discuss a complementary processing methodology, the cone kernel time-frequency representation, that, although slightly suboptimal in a detection sense, yields simultaneously good resolution in time and frequency (range and Doppler). This processing may provide improved performance for target classification, especially in low signal-to-noise (SNR) environments, where the cone kernel processing outperforms the matched filter in Doppler estimation.<<ETX>>","PeriodicalId":289986,"journal":{"name":"[1991] IEEE Pacific Rim Conference on Communications, Computers and Signal Processing Conference Proceedings","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] IEEE Pacific Rim Conference on Communications, Computers and Signal Processing Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACRIM.1991.160861","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
Range-Doppler processing is the primary tool in active sonar and radar imaging. The matched-filter is the optimal detector in sonar and radar, but has drawbacks in time and frequency resolution which may hinder its performance as a classifier. The authors discuss a complementary processing methodology, the cone kernel time-frequency representation, that, although slightly suboptimal in a detection sense, yields simultaneously good resolution in time and frequency (range and Doppler). This processing may provide improved performance for target classification, especially in low signal-to-noise (SNR) environments, where the cone kernel processing outperforms the matched filter in Doppler estimation.<>