Robust localization under NLOS environment in the presence of isolated outliers by full-Set TDOA measurements
•Closed-form TDOA algorithm for the full set.•Theoretical analysis for the proposed TDOA algorithm for Gaussian noise over the small error region.•Capability of rejecting NLOS-path measurements with attractive computational efficiency. Different from the traditional approach of using the reduced set...
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| Published in | Signal processing Vol. 212; p. 109159 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.11.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0165-1684 1872-7557 |
| DOI | 10.1016/j.sigpro.2023.109159 |
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| Abstract | •Closed-form TDOA algorithm for the full set.•Theoretical analysis for the proposed TDOA algorithm for Gaussian noise over the small error region.•Capability of rejecting NLOS-path measurements with attractive computational efficiency.
Different from the traditional approach of using the reduced set of time-difference-of-arrival (TDOA) measurements, localization by the full TDOA set is discussed here. It avoids choosing a specific reference sensor and exploits more measurements, conferring robustness against outliers. Nevertheless, the none-line-of-sight (NLOS) propagation still presents challenges for the existing full-set positioning algorithms. In this work, we develop an iterative scheme that utilizes the full TDOA measurements for localization capable of simultaneously mitigating the influence of outliers and NLOS-path measurements. The proposed scheme consists of the localization and identification modules, and they are designed with low complexity to meet real-time positioning demands. The theoretical optimal TDOA methods using full-set measurements are proposed in the localization module. Besides, to identify the NLOS measurements, the identification module adopts a greedy search-based random sample consensus (GS-RSC) algorithm. It can work cooperatively with the proposed lightweight localization module, returning a set free of outliers, NLOS measurements, and an accurate source location estimate. The theoretical analysis and experiments illustrate the superiority of the proposed scheme over the state-of-the-art TDOA full-set algorithms for handling outliers and NLOS measurements in localization. |
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| AbstractList | •Closed-form TDOA algorithm for the full set.•Theoretical analysis for the proposed TDOA algorithm for Gaussian noise over the small error region.•Capability of rejecting NLOS-path measurements with attractive computational efficiency.
Different from the traditional approach of using the reduced set of time-difference-of-arrival (TDOA) measurements, localization by the full TDOA set is discussed here. It avoids choosing a specific reference sensor and exploits more measurements, conferring robustness against outliers. Nevertheless, the none-line-of-sight (NLOS) propagation still presents challenges for the existing full-set positioning algorithms. In this work, we develop an iterative scheme that utilizes the full TDOA measurements for localization capable of simultaneously mitigating the influence of outliers and NLOS-path measurements. The proposed scheme consists of the localization and identification modules, and they are designed with low complexity to meet real-time positioning demands. The theoretical optimal TDOA methods using full-set measurements are proposed in the localization module. Besides, to identify the NLOS measurements, the identification module adopts a greedy search-based random sample consensus (GS-RSC) algorithm. It can work cooperatively with the proposed lightweight localization module, returning a set free of outliers, NLOS measurements, and an accurate source location estimate. The theoretical analysis and experiments illustrate the superiority of the proposed scheme over the state-of-the-art TDOA full-set algorithms for handling outliers and NLOS measurements in localization. |
| ArticleNumber | 109159 |
| Author | Wang, Zhi Ho, K.C. Wang, Yuwei |
| Author_xml | – sequence: 1 givenname: Yuwei surname: Wang fullname: Wang, Yuwei organization: College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, Zhejiang Province, China – sequence: 2 givenname: K.C. surname: Ho fullname: Ho, K.C. organization: Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, U.S.A – sequence: 3 givenname: Zhi surname: Wang fullname: Wang, Zhi email: zjuwangzhi@zju.edu.cn organization: College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, Zhejiang Province, China |
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| Keywords | Time-Difference-of-Arrival (TDOA) Cramér-Rao lower bound (CRLB) Full TDOA set Source localization None-light-of-sight (NLOS) identification |
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| SubjectTerms | Cramér-Rao lower bound (CRLB) Full TDOA set None-light-of-sight (NLOS) identification Source localization Time-Difference-of-Arrival (TDOA) |
| Title | Robust localization under NLOS environment in the presence of isolated outliers by full-Set TDOA measurements |
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