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Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm

Time difference of arrival (TDoA) based on a group of sensor nodes with known locations has been widely used to locate targets. Two-step weighted least squares (TSWLS), constrained weighted least squares (CWLS), and Newton–Raphson (NR) iteration are commonly used passive location methods, among whic...

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Autores principales: Wu, Peng, Su, Shaojing, Zuo, Zhen, Guo, Xiaojun, Sun, Bei, Wen, Xudong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603714/
https://www.ncbi.nlm.nih.gov/pubmed/31167498
http://dx.doi.org/10.3390/s19112554
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author Wu, Peng
Su, Shaojing
Zuo, Zhen
Guo, Xiaojun
Sun, Bei
Wen, Xudong
author_facet Wu, Peng
Su, Shaojing
Zuo, Zhen
Guo, Xiaojun
Sun, Bei
Wen, Xudong
author_sort Wu, Peng
collection PubMed
description Time difference of arrival (TDoA) based on a group of sensor nodes with known locations has been widely used to locate targets. Two-step weighted least squares (TSWLS), constrained weighted least squares (CWLS), and Newton–Raphson (NR) iteration are commonly used passive location methods, among which the initial position is needed and the complexity is high. This paper proposes a hybrid firefly algorithm (hybrid-FA) method, combining the weighted least squares (WLS) algorithm and FA, which can reduce computation as well as achieve high accuracy. The WLS algorithm is performed first, the result of which is used to restrict the search region for the FA method. Simulations showed that the hybrid-FA method required far fewer iterations than the FA method alone to achieve the same accuracy. Additionally, two experiments were conducted to compare the results of hybrid-FA with other methods. The findings indicated that the root-mean-square error (RMSE) and mean distance error of the hybrid-FA method were lower than that of the NR, TSWLS, and genetic algorithm (GA). On the whole, the hybrid-FA outperformed the NR, TSWLS, and GA for TDoA measurement.
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spelling pubmed-66037142019-07-17 Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm Wu, Peng Su, Shaojing Zuo, Zhen Guo, Xiaojun Sun, Bei Wen, Xudong Sensors (Basel) Article Time difference of arrival (TDoA) based on a group of sensor nodes with known locations has been widely used to locate targets. Two-step weighted least squares (TSWLS), constrained weighted least squares (CWLS), and Newton–Raphson (NR) iteration are commonly used passive location methods, among which the initial position is needed and the complexity is high. This paper proposes a hybrid firefly algorithm (hybrid-FA) method, combining the weighted least squares (WLS) algorithm and FA, which can reduce computation as well as achieve high accuracy. The WLS algorithm is performed first, the result of which is used to restrict the search region for the FA method. Simulations showed that the hybrid-FA method required far fewer iterations than the FA method alone to achieve the same accuracy. Additionally, two experiments were conducted to compare the results of hybrid-FA with other methods. The findings indicated that the root-mean-square error (RMSE) and mean distance error of the hybrid-FA method were lower than that of the NR, TSWLS, and genetic algorithm (GA). On the whole, the hybrid-FA outperformed the NR, TSWLS, and GA for TDoA measurement. MDPI 2019-06-04 /pmc/articles/PMC6603714/ /pubmed/31167498 http://dx.doi.org/10.3390/s19112554 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wu, Peng
Su, Shaojing
Zuo, Zhen
Guo, Xiaojun
Sun, Bei
Wen, Xudong
Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm
title Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm
title_full Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm
title_fullStr Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm
title_full_unstemmed Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm
title_short Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm
title_sort time difference of arrival (tdoa) localization combining weighted least squares and firefly algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603714/
https://www.ncbi.nlm.nih.gov/pubmed/31167498
http://dx.doi.org/10.3390/s19112554
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