Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty Term

This paper considers the time-of-arrival (TOA) based source localization problems when the start transmission time is unknown for both cases of accurate and inaccurate sensor locations. For the case where the sensor locations are accurate, the weighted least squares (WLS) criterion is adopted, leadi...

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Main Authors: Ruichao Zheng, Jinliang Dong, Zhao Han, Wen Xi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/11097306/
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author Ruichao Zheng
Jinliang Dong
Zhao Han
Wen Xi
author_facet Ruichao Zheng
Jinliang Dong
Zhao Han
Wen Xi
author_sort Ruichao Zheng
collection DOAJ
description This paper considers the time-of-arrival (TOA) based source localization problems when the start transmission time is unknown for both cases of accurate and inaccurate sensor locations. For the case where the sensor locations are accurate, the weighted least squares (WLS) criterion is adopted, leading to a constrained weighted least squares (CWLS) problem. By using the convex relaxation technique, the CWLS problem is relaxed into a novel quasi-convex fractional programming (FP) problem, which is then transformed into an equivalent mixed semi-definite and second-order cone programming (SD/SOCP) problem. This SD/SOCP problem is further tightened by adding a series of second-order cone constraints and a penalty term. For the case where the sensor locations are inaccurate, Taylor series expansion is applied to formulate the new expression of the error term, resulting in the CWLS problem considering the sensor location errors. The solution of this problem can be approximately obtained through similar operations. The results from the simulations and experiments confirm the proposed method can achieve the Cramer-Rao lower bound (CRLB) accuracy and possess a good robustness against the selection of the penalty factor.
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institution Kabale University
issn 2169-3536
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publishDate 2025-01-01
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spelling doaj-art-710756c77d354fc0955aeaf65d43f6dd2025-08-20T03:45:03ZengIEEEIEEE Access2169-35362025-01-011313331013332010.1109/ACCESS.2025.359292611097306Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty TermRuichao Zheng0https://orcid.org/0009-0001-1436-4839Jinliang Dong1Zhao Han2Wen Xi3Nanjing Glarun Defense System Company Ltd., Nanjing, Jiangsu, ChinaNanjing Glarun Defense System Company Ltd., Nanjing, Jiangsu, ChinaNanjing Glarun Defense System Company Ltd., Nanjing, Jiangsu, ChinaNanjing Glarun Defense System Company Ltd., Nanjing, Jiangsu, ChinaThis paper considers the time-of-arrival (TOA) based source localization problems when the start transmission time is unknown for both cases of accurate and inaccurate sensor locations. For the case where the sensor locations are accurate, the weighted least squares (WLS) criterion is adopted, leading to a constrained weighted least squares (CWLS) problem. By using the convex relaxation technique, the CWLS problem is relaxed into a novel quasi-convex fractional programming (FP) problem, which is then transformed into an equivalent mixed semi-definite and second-order cone programming (SD/SOCP) problem. This SD/SOCP problem is further tightened by adding a series of second-order cone constraints and a penalty term. For the case where the sensor locations are inaccurate, Taylor series expansion is applied to formulate the new expression of the error term, resulting in the CWLS problem considering the sensor location errors. The solution of this problem can be approximately obtained through similar operations. The results from the simulations and experiments confirm the proposed method can achieve the Cramer-Rao lower bound (CRLB) accuracy and possess a good robustness against the selection of the penalty factor.https://ieeexplore.ieee.org/document/11097306/Time-of-arrival (TOA)localizationfractional programming (FP)semi-definite and second-order cone programming (SD/SOCP)sensor location errors
spellingShingle Ruichao Zheng
Jinliang Dong
Zhao Han
Wen Xi
Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty Term
IEEE Access
Time-of-arrival (TOA)
localization
fractional programming (FP)
semi-definite and second-order cone programming (SD/SOCP)
sensor location errors
title Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty Term
title_full Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty Term
title_fullStr Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty Term
title_full_unstemmed Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty Term
title_short Robust Time-of-Arrival-Based Localization With Unknown Transmission Time Using Convex Relaxation and Penalty Term
title_sort robust time of arrival based localization with unknown transmission time using convex relaxation and penalty term
topic Time-of-arrival (TOA)
localization
fractional programming (FP)
semi-definite and second-order cone programming (SD/SOCP)
sensor location errors
url https://ieeexplore.ieee.org/document/11097306/
work_keys_str_mv AT ruichaozheng robusttimeofarrivalbasedlocalizationwithunknowntransmissiontimeusingconvexrelaxationandpenaltyterm
AT jinliangdong robusttimeofarrivalbasedlocalizationwithunknowntransmissiontimeusingconvexrelaxationandpenaltyterm
AT zhaohan robusttimeofarrivalbasedlocalizationwithunknowntransmissiontimeusingconvexrelaxationandpenaltyterm
AT wenxi robusttimeofarrivalbasedlocalizationwithunknowntransmissiontimeusingconvexrelaxationandpenaltyterm