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Open AccessArticle

Analysis of Sources of Large Positioning Errors in Deterministic Fingerprinting

by Joaquín Torres-Sospedra 1,*,† and Adriano Moreira 2,*,†
Institute of New Imaging Technologies, Universitat Jaume I, 12071 Castellón de la Plana, Spain
Algoritmi Research Centre, University of Minho, 4800-058 Guimarães, Portugal
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2017, 17(12), 2736;
Received: 31 October 2017 / Revised: 22 November 2017 / Accepted: 23 November 2017 / Published: 27 November 2017
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. View Full-Text
Keywords: indoor positioning; Wi-Fi fingerprinting; simulation; positioning errors indoor positioning; Wi-Fi fingerprinting; simulation; positioning errors
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Torres-Sospedra, J.; Moreira, A. Analysis of Sources of Large Positioning Errors in Deterministic Fingerprinting. Sensors 2017, 17, 2736.

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