Fengrui Zhang, Mingbing Li, Yimao Sun, Jifeng Zou, Q. Wan
{"title":"A TDOA-FDOA Localization Method in Closed-form Based on Deviation Refining","authors":"Fengrui Zhang, Mingbing Li, Yimao Sun, Jifeng Zou, Q. Wan","doi":"10.1109/WCSP.2019.8928125","DOIUrl":null,"url":null,"abstract":"This paper focuses on localizing a moving source with time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements in a wireless sensor network. An improved two-stage weighted least squares closed-form solution is proposed. The weighted spherical-interpolation method and deviation refining method are applied in the first and second stage respectively. It is analytically verified that the performance of proposed solution can attain the Cramér-Rao lower bound under mild Gaussian noise assumption. The proposed solution is shown to be effective and significantly decreases the bias of the estimate in terms of numerical simulations.","PeriodicalId":108635,"journal":{"name":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSP.2019.8928125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper focuses on localizing a moving source with time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements in a wireless sensor network. An improved two-stage weighted least squares closed-form solution is proposed. The weighted spherical-interpolation method and deviation refining method are applied in the first and second stage respectively. It is analytically verified that the performance of proposed solution can attain the Cramér-Rao lower bound under mild Gaussian noise assumption. The proposed solution is shown to be effective and significantly decreases the bias of the estimate in terms of numerical simulations.