Context Aware Mobile Personal Navigation Services Using Multi-Level Sensor Fusion

S. Saeedi, N. El-Sheimy, X. Zhao, Z. Sayed

Abstract:	Human movement makes personal navigation system (PNS) a challenging topic which as compared to other navigation platforms. Therefore, using customized and context-aware navigation services which are capable of detecting the user activity and device placement is necessary for various aspects of personal mobile navigation services. The main issue in such systems is detecting available context information using embedded mobile sensors in an implicit way. The proposed system in this research can detect user activity modes (e.g.walking, stationary, driving, and etc.) and the placement of the mobile device (e.g. in hand, on the belt, and etc.) to find the most appropriate navigation solution. The context detection algorithm proposed in this study is based on a multi-level sensor fusion algorithm which will improve the current intelligent navigation context detection solutions in the following ways: feature-level integration of multi-sensor data coming from different device sensors such as accelerometer and gyroscope using pattern recognition techniques (e.g. ANN), and high-level information fusion to detect context information from multiple information sources using knowledge discovery techniques (e.g. fuzzy inference system). Extensive pedestrian field tests have been performed using a portable prototype device developed by the MMSS research group at the University of Calgary. These tests have proved that the hybrid multi-level sensor fusion algorithm improves the mean total accuracy from 85% to 97% for user motions and device placement.
Published in:	Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011) September 20 - 23, 2011 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	1394 - 1403
Cite this article:	Saeedi, S., El-Sheimy, N., Zhao, X., Sayed, Z., "Context Aware Mobile Personal Navigation Services Using Multi-Level Sensor Fusion," Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011), Portland, OR, September 2011, pp. 1394-1403.
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