Piyush Kumar, Tathagata Mukherjee, E. Pasiliao, Liqin Xu
{"title":"Cheap approximate localization using FM radio","authors":"Piyush Kumar, Tathagata Mukherjee, E. Pasiliao, Liqin Xu","doi":"10.1145/2820783.2820868","DOIUrl":null,"url":null,"abstract":"In this paper, we present a coarse and passive localization system for GPS-denied environments. Our system is based on a cheap software defined radio (SDR) costing less than $25, which is used to listen to broadcast signals from local FM Radio stations. We show that the hardware and associated algorithms are capable of localizations with average errors of less than 5 miles, without requiring a fingerprinting or crowd sourcing approach. The algorithm is based on a large-scale simulation based map building phase and a query phase. We use 924 power spectra distributed over more than 200 miles for experimentally validating our query algorithm. Our average localization error is less than 5 miles.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"155 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2820783.2820868","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
In this paper, we present a coarse and passive localization system for GPS-denied environments. Our system is based on a cheap software defined radio (SDR) costing less than $25, which is used to listen to broadcast signals from local FM Radio stations. We show that the hardware and associated algorithms are capable of localizations with average errors of less than 5 miles, without requiring a fingerprinting or crowd sourcing approach. The algorithm is based on a large-scale simulation based map building phase and a query phase. We use 924 power spectra distributed over more than 200 miles for experimentally validating our query algorithm. Our average localization error is less than 5 miles.