{"title":"Effect of clutter topology on multi-hop localizer placement","authors":"M. Hussain, A. Trigoni","doi":"10.1109/WIOPT.2014.6850307","DOIUrl":null,"url":null,"abstract":"Accuracy in range-based localization systems can degrade rapidly in the presence of clutter in the environment. This is due to the incidence of Non-Line-of-Sight (NLOS) distance measurements between the anchors and an unlocalized node. While a large corpus of research work dealt with the scenario where the NLOS distances form a minority of the total distances to anchors, there has been not much research done to handle the situation where a majority or even all distance measurements to anchors are NLOS in nature. In our previous work, we showed that using localizers in a cluttered environment can improve the localization accuracy of a target node even when all the distance measurements are NLOS. Instead of NLOS bias, these techniques suffer residual multi-hop error, which is caused due to the distance overestimate when a multi-hop chain is used instead of the straight-line distance. In this paper, we analyze the effect of clutter topology on the multi-hop error. We use machine learning techniques to estimate the aggregate forms of the multi-hop error for a given clutter topology when only characteristic features of the clutter topology are provided.","PeriodicalId":381489,"journal":{"name":"2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIOPT.2014.6850307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Accuracy in range-based localization systems can degrade rapidly in the presence of clutter in the environment. This is due to the incidence of Non-Line-of-Sight (NLOS) distance measurements between the anchors and an unlocalized node. While a large corpus of research work dealt with the scenario where the NLOS distances form a minority of the total distances to anchors, there has been not much research done to handle the situation where a majority or even all distance measurements to anchors are NLOS in nature. In our previous work, we showed that using localizers in a cluttered environment can improve the localization accuracy of a target node even when all the distance measurements are NLOS. Instead of NLOS bias, these techniques suffer residual multi-hop error, which is caused due to the distance overestimate when a multi-hop chain is used instead of the straight-line distance. In this paper, we analyze the effect of clutter topology on the multi-hop error. We use machine learning techniques to estimate the aggregate forms of the multi-hop error for a given clutter topology when only characteristic features of the clutter topology are provided.