Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/48379

TitleAnalysis of sources of large positioning errors in deterministic fingerprinting
Author(s)Torres-Sospedra, Joaquín
Moreira, Adriano
Keywordsindoor positioning
Wi-Fi fingerprinting
simulation
positioning errors
Issue date27-Nov-2017
PublisherMDPI
JournalSensors
CitationTorres-Sospedra, J., & Moreira, A. (2017). Analysis of Sources of Large Positioning Errors in Deterministic Fingerprinting. Sensors, 17(12), 2736.
Abstract(s)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.
TypeArticle
URIhttp://hdl.handle.net/1822/48379
DOI10.3390/s17122736
ISSN1424-8220
Publisher versionhttp://www.mdpi.com/1424-8220/17/12/2736
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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