{"title":"Range-based geolocation in fading environments","authors":"B. Sadler, Ning Liu, Zhengyuan Xu, R. Kozick","doi":"10.1109/ALLERTON.2008.4797529","DOIUrl":null,"url":null,"abstract":"We consider source geolocation based on range estimates from sensors with known coordinates. In a fading propagation environment, where a line-of-sight (LOS) path may be weak or essentially nonexistent, range estimates may have positive biases. We study this problem by considering a weighted least squares (WLS) location estimator, based on noisy range estimates, each of which is contaminated by additive Gaussian noise and possibly a positive bias. We derive the mean and mean-square error (MSE) of the WLS estimator, showing that in general the estimator produces biased estimates. The error expressions are developed via first-order perturbation analysis. They provide a means to study achievable localization performance, as a function of the measurement bias and variance, as well as the sensor network geometry.","PeriodicalId":120561,"journal":{"name":"2008 46th Annual Allerton Conference on Communication, Control, and Computing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 46th Annual Allerton Conference on Communication, Control, and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ALLERTON.2008.4797529","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
We consider source geolocation based on range estimates from sensors with known coordinates. In a fading propagation environment, where a line-of-sight (LOS) path may be weak or essentially nonexistent, range estimates may have positive biases. We study this problem by considering a weighted least squares (WLS) location estimator, based on noisy range estimates, each of which is contaminated by additive Gaussian noise and possibly a positive bias. We derive the mean and mean-square error (MSE) of the WLS estimator, showing that in general the estimator produces biased estimates. The error expressions are developed via first-order perturbation analysis. They provide a means to study achievable localization performance, as a function of the measurement bias and variance, as well as the sensor network geometry.