Simultaneous localization and mapping for pedestrians using only foot-mounted inertial sensors
Proceedings of the 11th international conference on Ubiquitous computing
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In this paper, we propose Social-Loc, which uniquely utilizes social interactions in addition to common on-board sensors such as accelerometer and gyroscope on modern smartphones, to localize indoor mobile users. Specifically, Social-Loc takes the potential locations for individual users estimated by a novel particle filter tailored for indoor localization as input, and exploits both social encounter and non-encounter events to further improve the localization accuracy. We have implemented Social-Loc on the Android platform and extensively evaluated its performance. The simulation results demonstrate that Social-Loc improves the accuracy of the particle-filter-only scheme by as much as 560% on average and is able to achieve accuracy of few meters without any external ranging device or system training.