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An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones

Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative...

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Detalles Bibliográficos
Autores principales: Li, Huaiyu, Chen, Xiuwan, Jing, Guifei, Wang, Yuan, Cao, Yanfeng, Li, Fei, Zhang, Xinlong, Xiao, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721770/
https://www.ncbi.nlm.nih.gov/pubmed/26690447
http://dx.doi.org/10.3390/s151229850
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author Li, Huaiyu
Chen, Xiuwan
Jing, Guifei
Wang, Yuan
Cao, Yanfeng
Li, Fei
Zhang, Xinlong
Xiao, Han
author_facet Li, Huaiyu
Chen, Xiuwan
Jing, Guifei
Wang, Yuan
Cao, Yanfeng
Li, Fei
Zhang, Xinlong
Xiao, Han
author_sort Li, Huaiyu
collection PubMed
description Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel “quasi-dynamic” Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the “process-level” fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move.
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spelling pubmed-47217702016-01-26 An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones Li, Huaiyu Chen, Xiuwan Jing, Guifei Wang, Yuan Cao, Yanfeng Li, Fei Zhang, Xinlong Xiao, Han Sensors (Basel) Article Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel “quasi-dynamic” Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the “process-level” fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move. MDPI 2015-12-11 /pmc/articles/PMC4721770/ /pubmed/26690447 http://dx.doi.org/10.3390/s151229850 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Huaiyu
Chen, Xiuwan
Jing, Guifei
Wang, Yuan
Cao, Yanfeng
Li, Fei
Zhang, Xinlong
Xiao, Han
An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones
title An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones
title_full An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones
title_fullStr An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones
title_full_unstemmed An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones
title_short An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones
title_sort indoor continuous positioning algorithm on the move by fusing sensors and wi-fi on smartphones
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721770/
https://www.ncbi.nlm.nih.gov/pubmed/26690447
http://dx.doi.org/10.3390/s151229850
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