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Hybrid Indoor Localization using GSM Fingerprints, Embedded Sensors and a Particle Filter

Abstract : 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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Conference papers
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https://hal.archives-ouvertes.fr/hal-01126520
Contributor : Laboratoire Cedric <>
Submitted on : Friday, March 6, 2015 - 11:59:40 AM
Last modification on : Saturday, September 26, 2020 - 11:44:10 PM

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  • HAL Id : hal-01126520, version 1

Citation

Ye Tian, Bruce Denby, Iness Ahriz, Pierre Roussel, Gérard Dreyfus. Hybrid Indoor Localization using GSM Fingerprints, Embedded Sensors and a Particle Filter. The Eleventh International Symposium on Wireless Communication Systems, Aug 2014, Barcelona, Spain. pp.542 - 547. ⟨hal-01126520⟩

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