1. Mass-centered weight update scheme for particle filter based indoor pedestrian positioning
- Author
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Haiyong Luo, Muhammad Zahid Tunio, Fang Zhao, Wenhua Shao, Cong Wang, and Antonino Crivello
- Subjects
Dynamic time warping ,Ubiquitous computing ,Indoor positioning ,Computer science ,Location awareness ,010401 analytical chemistry ,Real-time computing ,020206 networking & telecommunications ,02 engineering and technology ,Pedestrian ,Fingerprint recognition ,01 natural sciences ,0104 chemical sciences ,Particle filter ,0202 electrical engineering, electronic engineering, information engineering ,Magnetic field based positioning - Abstract
Smartphone based indoor positioning has become a hot topic in pervasive computing, because of the need to improve indoor location-based services. In order to strengthen positioning accuracy, researchers have tried to leverage high-resolution magnetic fingerprint with particle filter and dynamic time warping (DTW). These approaches are computation-hungry, which increases hardware cost for positioning companies. By analyzing magnetic features for pedestrian users, we present a mass-centered weight update scheme to decrease calculation overheads. Finally, the proposed positioning algorithm is tested in a realistic situation, showing high-quality localization capability.
- Published
- 2018