Hybrid indoor localization using GSM fingerprints, embedded sensors and a particle filter

The article presents an indoor localization scheme for mobile devices based on GSM Received Signal Strength fingerprints combined with embedded sensor information and an area site map. Displacements of a mobile user are first estimated using a sensor dead-reckoning approach that adapts stride length to different users and environments, and a dynamically switched orientation estimation scheme responding to orientation changes of the mobile device. Positions derived from GSM fingerprints, along with constraints imposed by a site map, are then integrated using a particle filter in order to prevent the accumulation of dead-reckoning errors over time. The study demonstrates that a standard handset with cellular network access and embedded inertial sensors can provide a good solution for indoor localization.

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