{"title":"TDE, DOA and related parameter estimation problems in impulsive noise","authors":"A. Swami, Brian M. Sadler","doi":"10.1109/HOST.1997.613530","DOIUrl":null,"url":null,"abstract":"We address the problem of time-delay estimation (TDE) and direction-of-arrival (DOA) estimation in the presence of symmetric alpha-stable noise. We show that these problems can be handled by conventional correlation or cumulant based techniques, provided that the noisy signals are first passed through a generic zero-memory non-linearity. This pre-processing is also useful in the detection context. We also address the problem of blind linear system identification, where the input is an iid alpha-stable process; we show that consistent estimates of the possibly non-minimum phase ARMA parameters can be obtained by using self-normalized correlations and cumulants. Theoretical arguments are supported by simulations.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"117 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
We address the problem of time-delay estimation (TDE) and direction-of-arrival (DOA) estimation in the presence of symmetric alpha-stable noise. We show that these problems can be handled by conventional correlation or cumulant based techniques, provided that the noisy signals are first passed through a generic zero-memory non-linearity. This pre-processing is also useful in the detection context. We also address the problem of blind linear system identification, where the input is an iid alpha-stable process; we show that consistent estimates of the possibly non-minimum phase ARMA parameters can be obtained by using self-normalized correlations and cumulants. Theoretical arguments are supported by simulations.