Analysis of sources of large positioning errors in deterministic fingerprinting
| Main Author: | |
|---|---|
| Publication Date: | 2017 |
| Other Authors: | |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://hdl.handle.net/1822/48379 |
Summary: | Wi-Fi fingerprinting is widely used for indoor positioning and indoor navigation due to the ubiquity of wireless networks, high proliferation of Wi-Fi-enabled mobile devices, and its reasonable positioning accuracy. The assumption is that the position can be estimated based on the received signal strength intensity from multiple wireless access points at a given point. The positioning accuracy, within a few meters, enables the use of Wi-Fi fingerprinting in many different applications. However, it has been detected that the positioning error might be very large in a few cases, which might prevent its use in applications with high accuracy positioning requirements. Hybrid methods are the new trend in indoor positioning since they benefit from multiple diverse technologies (Wi-Fi, Bluetooth, and Inertial Sensors, among many others) and, therefore, they can provide a more robust positioning accuracy. In order to have an optimal combination of technologies, it is crucial to identify when large errors occur and prevent the use of extremely bad positioning estimations in hybrid algorithms. This paper investigates why large positioning errors occur in Wi-Fi fingerprinting and how to detect them by using the received signal strength intensities. |
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Analysis of sources of large positioning errors in deterministic fingerprintingindoor positioningWi-Fi fingerprintingsimulationpositioning errorsEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaScience & TechnologyWi-Fi fingerprinting is widely used for indoor positioning and indoor navigation due to the ubiquity of wireless networks, high proliferation of Wi-Fi-enabled mobile devices, and its reasonable positioning accuracy. The assumption is that the position can be estimated based on the received signal strength intensity from multiple wireless access points at a given point. The positioning accuracy, within a few meters, enables the use of Wi-Fi fingerprinting in many different applications. However, it has been detected that the positioning error might be very large in a few cases, which might prevent its use in applications with high accuracy positioning requirements. Hybrid methods are the new trend in indoor positioning since they benefit from multiple diverse technologies (Wi-Fi, Bluetooth, and Inertial Sensors, among many others) and, therefore, they can provide a more robust positioning accuracy. In order to have an optimal combination of technologies, it is crucial to identify when large errors occur and prevent the use of extremely bad positioning estimations in hybrid algorithms. This paper investigates why large positioning errors occur in Wi-Fi fingerprinting and how to detect them by using the received signal strength intensities.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT-Fundação para a Ciência e Tecnologia within the scope of project UID/CEC/00319/2013, by the Portugal Incentive System for Research and Technological Development in the scope of the projects in co-promotion no 002814/2015 (iFACTORY 2015-2018)info:eu-repo/semantics/publishedVersionMDPIUniversidade do MinhoTorres-Sospedra, JoaquínMoreira, Adriano2017-11-272017-11-27T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/48379engTorres-Sospedra, J., & Moreira, A. (2017). Analysis of Sources of Large Positioning Errors in Deterministic Fingerprinting. Sensors, 17(12), 2736.1424-822010.3390/s1712273629186921http://www.mdpi.com/1424-8220/17/12/2736info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:14:58Zoai:repositorium.sdum.uminho.pt:1822/48379Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:20:37.253498Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Analysis of sources of large positioning errors in deterministic fingerprinting |
| title |
Analysis of sources of large positioning errors in deterministic fingerprinting |
| spellingShingle |
Analysis of sources of large positioning errors in deterministic fingerprinting Torres-Sospedra, Joaquín indoor positioning Wi-Fi fingerprinting simulation positioning errors Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology |
| title_short |
Analysis of sources of large positioning errors in deterministic fingerprinting |
| title_full |
Analysis of sources of large positioning errors in deterministic fingerprinting |
| title_fullStr |
Analysis of sources of large positioning errors in deterministic fingerprinting |
| title_full_unstemmed |
Analysis of sources of large positioning errors in deterministic fingerprinting |
| title_sort |
Analysis of sources of large positioning errors in deterministic fingerprinting |
| author |
Torres-Sospedra, Joaquín |
| author_facet |
Torres-Sospedra, Joaquín Moreira, Adriano |
| author_role |
author |
| author2 |
Moreira, Adriano |
| author2_role |
author |
| dc.contributor.none.fl_str_mv |
Universidade do Minho |
| dc.contributor.author.fl_str_mv |
Torres-Sospedra, Joaquín Moreira, Adriano |
| dc.subject.por.fl_str_mv |
indoor positioning Wi-Fi fingerprinting simulation positioning errors Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology |
| topic |
indoor positioning Wi-Fi fingerprinting simulation positioning errors Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology |
| description |
Wi-Fi fingerprinting is widely used for indoor positioning and indoor navigation due to the ubiquity of wireless networks, high proliferation of Wi-Fi-enabled mobile devices, and its reasonable positioning accuracy. The assumption is that the position can be estimated based on the received signal strength intensity from multiple wireless access points at a given point. The positioning accuracy, within a few meters, enables the use of Wi-Fi fingerprinting in many different applications. However, it has been detected that the positioning error might be very large in a few cases, which might prevent its use in applications with high accuracy positioning requirements. Hybrid methods are the new trend in indoor positioning since they benefit from multiple diverse technologies (Wi-Fi, Bluetooth, and Inertial Sensors, among many others) and, therefore, they can provide a more robust positioning accuracy. In order to have an optimal combination of technologies, it is crucial to identify when large errors occur and prevent the use of extremely bad positioning estimations in hybrid algorithms. This paper investigates why large positioning errors occur in Wi-Fi fingerprinting and how to detect them by using the received signal strength intensities. |
| publishDate |
2017 |
| dc.date.none.fl_str_mv |
2017-11-27 2017-11-27T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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http://hdl.handle.net/1822/48379 |
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http://hdl.handle.net/1822/48379 |
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eng |
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eng |
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Torres-Sospedra, J., & Moreira, A. (2017). Analysis of Sources of Large Positioning Errors in Deterministic Fingerprinting. Sensors, 17(12), 2736. 1424-8220 10.3390/s17122736 29186921 http://www.mdpi.com/1424-8220/17/12/2736 |
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