XINS: the anatomy of an indoor positioning and navigation architecture

Location-Based Service (LBS) is becoming a ubiquitous technology for mobile devices. In this work, we propose a signal-fusion architecture called XINS to perform effective indoor positioning and navigation. XINS uses signals from inertial navigation units as well as WiFi and floor-map constraints to detect turns, estimate travel distances, and predict locations. XINS employs non-intrusive calibration procedures to significantly reduce errors, and fuses signals synergistically to improve computational efficiency, enhance location-prediction accuracy, and conserve power.

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