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Subway Station Real-time Indoor Positioning System for Cell Phones

Ma, C; Wan, C; Chau, Y; Kang, S; Selviah, D; (2017) Subway Station Real-time Indoor Positioning System for Cell Phones. In: Proceedings of the 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE: Sapporo, Japan. Green open access

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Abstract

As wireless local area network, WLAN, access point (AP) are becoming very common wireless communication infrastructures in indoor environments, Wi-Fi signal based Indoor Positioning Systems (IPS) have been widely developed in recent years and one of the most popular technologies is the received signal strength (RSS) fingerprinting technology. However, due to large amount of time-consuming work required for offline calibration in large indoor environments, researchers have investigated generating the calibration database while walking about instead of carrying out measurements over a time period at fixed reference points [1]. This paper combines both Wi-Fi fingerprinting and Pedestrian Dead-reckoning (PDR) technologies to introduce a real-time indoor navigation system for large complex three-dimensional indoor environments including a novel calibration method with associated novel matching algorithms. Detailed experiments were conducted in two subway stations with complicated structure under normal operating conditions in which trains regularly arrived and departed and groups of people walked to and from the trains. The results for real cell phone tracking on phones carried by passengers, give a satisfactory error of 2.9 metres during peak congestion times and 1.7 metres when few people were in the station.

Type: Proceedings paper
Title: Subway Station Real-time Indoor Positioning System for Cell Phones
Event: 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
Location: Sapporo, Japan
Dates: 18 September 2017 - 21 September 2017
ISBN-13: 9781509062997
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/IPIN.2017.8115912
Publisher version: https://doi.org/10.1109/IPIN.2017.8115912
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Fingerprint recognition, Calibration, Wireless fidelity, Legged locomotion, Databases, Public transportation, Smart phones, Wi-Fi fingerprinting, Pedestrian Dead-reckoning (PDR), indoor positioning system (IPS), Kalman Filter, Power strength histogram, subway station, signal processing
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management
URI: https://discovery.ucl.ac.uk/id/eprint/1561272
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