{"title":"Time Delay Estimation for Noise-Like Signals Embedded in Non-Gaussian Noise Using Pre-filtering in Channels","authors":"V. Oliinyk, V. Lukin","doi":"10.1109/TCSET49122.2020.235510","DOIUrl":null,"url":null,"abstract":"A task of time delay estimation for two sensors that receive a noise-like wideband signal embedded in non-Gaussian environment is studied. One peculiarity of time delay estimates for conventional method of cross-correlation data processing is that they can be abnormal due to intensive noise influence and a limited interval of signal observation. Performance can be improved by pre-filtering of signal/noise mixtures in both channels. In addition to center weighted median filter proposed earlier, we consider application of 1-D filter based on discrete cosine transform (DCT). It is shown that the use of such a combination of center-weighted median and DCT-based filters provides more robust estimation in conditions of low signal-tonoise ratios (SNRs).","PeriodicalId":389689,"journal":{"name":"2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TCSET49122.2020.235510","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
A task of time delay estimation for two sensors that receive a noise-like wideband signal embedded in non-Gaussian environment is studied. One peculiarity of time delay estimates for conventional method of cross-correlation data processing is that they can be abnormal due to intensive noise influence and a limited interval of signal observation. Performance can be improved by pre-filtering of signal/noise mixtures in both channels. In addition to center weighted median filter proposed earlier, we consider application of 1-D filter based on discrete cosine transform (DCT). It is shown that the use of such a combination of center-weighted median and DCT-based filters provides more robust estimation in conditions of low signal-tonoise ratios (SNRs).