XINS: the anatomy of an indoor positioning and navigation architecture

Authors:
Yuan Gao;Qingxuan Yang;Guanfeng Li;Edward Y. Chang;Dong Wang;Chengu Wang;Hang Qu;Pei Dong;Faen Zhang
Affiliations:
Tsinghua University, Beijing, China;Google Research, Beijing, China;Google Research, Beijing, China;Google Research, Beijing, China;Google Research, Beijing, China;Tsinghua University, Beijing, China;Google Research, Beijing, China;Google Research, Beijing, China;Google Research, Beijing, China
Venue:
Proceedings of the 1st international workshop on Mobile location-based service
Year:
2011

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Abstract

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.