{"title":"Cooperative Positioning of Wireless Networks in Complex Propagation Environments","authors":"Peiyue Jiang;Xiaobo Gu;Haibo Zhou","doi":"10.1109/JSAC.2024.3414589","DOIUrl":null,"url":null,"abstract":"Cooperative positioning in wireless networks has attracted great attention in recent years, as many applications require the exact location of all member nodes. The pairwise distance between the member nodes is conventionally constructed as an Euclidean Distance Matrix (EDM) for subsequent location estimation. In this paper, we address the problem of cooperative positioning in complex propagation environments, which results in an incomplete EDM. We proposed an improved EDM recovery algorithm based on low tank matrix completion (LRMC), which makes use of the sensor correlation by Laplacian and trace minimization. In addition, we derive a semi-definite relaxation estimator to localize the unknown sensors. Simulations are conducted to evaluate the performance of the proposed algorithm and the results show that the proposed method outperforms existing ones in both matrix completion and positioning accuracy.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"42 10","pages":"2877-2889"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10557659/","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
Cooperative positioning in wireless networks has attracted great attention in recent years, as many applications require the exact location of all member nodes. The pairwise distance between the member nodes is conventionally constructed as an Euclidean Distance Matrix (EDM) for subsequent location estimation. In this paper, we address the problem of cooperative positioning in complex propagation environments, which results in an incomplete EDM. We proposed an improved EDM recovery algorithm based on low tank matrix completion (LRMC), which makes use of the sensor correlation by Laplacian and trace minimization. In addition, we derive a semi-definite relaxation estimator to localize the unknown sensors. Simulations are conducted to evaluate the performance of the proposed algorithm and the results show that the proposed method outperforms existing ones in both matrix completion and positioning accuracy.