Arghavan Amini, R. Vaghefi, J. M. Garza, R. Buehrer
{"title":"GPS-free cooperative mobile tracking with the application in vehicular networks","authors":"Arghavan Amini, R. Vaghefi, J. M. Garza, R. Buehrer","doi":"10.1109/WPNC.2014.6843293","DOIUrl":null,"url":null,"abstract":"In this paper, the problem of mobile tracking in dense environments is studied. The Global Positioning System (GPS) is the most accessible positioning technique. However, GPS does not work properly in indoor and dense areas, as the receiver typically does not have access to a sufficient number of line-of-sight satellites. Therefore, localization in these networks can be alternatively done by using measurements collected within the network and without the aid of any external resources (e.g., GPS). The mobile tracking problem includes several static reference nodes whose locations are fixed and known, and many mobile nodes whose locations are unknown and needed to be determined. The problem of mobile tracking can be solved in two forms: centralized and distributed. A centralized algorithm can result in high complexity and latency, while a distributed algorithm might lead to large estimation errors. In this paper, a novel cooperative localization technique is introduced which is able to deliver a promising localization accuracy while maintain the latency and complexity as low as possible. The performance of the proposed algorithm is compared with those of other algorithms in terms of localization accuracy, latency, and required data communication through computer simulations. The simulation results show the effectiveness of the proposed algorithm in comparison with either centralized and distributed algorithms. An important application of this work is vehicle localization in dense environments where the vehicles do not have access to GPS satellites and must be localized by the elements within the network.","PeriodicalId":106193,"journal":{"name":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 11th Workshop on Positioning, Navigation and Communication (WPNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WPNC.2014.6843293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
In this paper, the problem of mobile tracking in dense environments is studied. The Global Positioning System (GPS) is the most accessible positioning technique. However, GPS does not work properly in indoor and dense areas, as the receiver typically does not have access to a sufficient number of line-of-sight satellites. Therefore, localization in these networks can be alternatively done by using measurements collected within the network and without the aid of any external resources (e.g., GPS). The mobile tracking problem includes several static reference nodes whose locations are fixed and known, and many mobile nodes whose locations are unknown and needed to be determined. The problem of mobile tracking can be solved in two forms: centralized and distributed. A centralized algorithm can result in high complexity and latency, while a distributed algorithm might lead to large estimation errors. In this paper, a novel cooperative localization technique is introduced which is able to deliver a promising localization accuracy while maintain the latency and complexity as low as possible. The performance of the proposed algorithm is compared with those of other algorithms in terms of localization accuracy, latency, and required data communication through computer simulations. The simulation results show the effectiveness of the proposed algorithm in comparison with either centralized and distributed algorithms. An important application of this work is vehicle localization in dense environments where the vehicles do not have access to GPS satellites and must be localized by the elements within the network.