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Collaborative Smartphone-Based User Positioning in a Multiple-User Context Using Wireless Technologies

By Viet-Cuong Ta, Trung-Kien Dao, Dominique Vaufreydaz and Eric Castelli

Abstract

International audienceFor the localization of multiple users, Bluetooth data from the smartphone is able to complement Wi-Fi-based methods with additional information, by providing an approximation of the relative distances between users. In practice, both positions provided by Wi-Fi data and relative distance provided by Bluetooth data are subject to a certain degree of noise due to the uncertainty of radio propagation in complex indoor environments. In this study, we propose and evaluate two approaches, namely Non-temporal and Temporal ones, of collaborative positioning to combine these two cohabiting technologies to improve the tracking performance. In the Non-temporal approach, our model establishes an error observation function in a specific interval of the Bluetooth and Wi-Fi output. It is then able to reduce the positioning error by looking for ways to minimize the error function. The Temporal approach employs an extended error model that takes into account the time component between users’ movements. For performance evaluation, several multi-user scenarios in an indoor environment are set up. Results show that for certain scenarios, the proposed approaches attain over 40% of improvement in terms of average accuracy

Topics: indoor localization, indoor navigation, multi-sensor fusion, multiple-user positioning, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing
Publisher: MDPI
Year: 2020
DOI identifier: 10.3390/s20020405
OAI identifier: oai:HAL:hal-02435610v1
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