{"title":"Worst-case Cramer-Rao bound for parametric estimation of superimposed signals","authors":"S. Yau, Y. Bresler","doi":"10.1109/SPECT.1990.205572","DOIUrl":null,"url":null,"abstract":"The problem of parameter estimation of superimposed signals in white Gaussian noise is considered and the effect of the amplitude correlation structure on the Cramer-Rao bounds is studied. The best and worst conditions are found using various criteria, and closed form expressions for the bounds, which are free from the nuisance parameters of correlation structure, are derived. The results are applied to the example of parameter estimation of superimposed sinusoids, or plan-wave direction finding in white Gaussian noise, determining best and worst conditions on the signal cross-correlation and relative phases.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPECT.1990.205572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The problem of parameter estimation of superimposed signals in white Gaussian noise is considered and the effect of the amplitude correlation structure on the Cramer-Rao bounds is studied. The best and worst conditions are found using various criteria, and closed form expressions for the bounds, which are free from the nuisance parameters of correlation structure, are derived. The results are applied to the example of parameter estimation of superimposed sinusoids, or plan-wave direction finding in white Gaussian noise, determining best and worst conditions on the signal cross-correlation and relative phases.<>