An adaptive hybrid filter for practical WiFi-based positioning systems

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This paper proposes an adaptive hybrid filter for WiFi-based indoor positioning systems. The hybrid filter adopts the notion of particle filters within the prediction framework of the basic Kalman filter. Restricting the predicts of a moving object to a small number of particles on a way network, and replacing the Kalman gain with a dynamic weighting scheme are the key features of the hybrid filter. The adaptive hybrid filter significantly outperformed the basic Kalman filter, and a particle filter in the performance evaluation at three test places: a Library and N5 building, KAIST, Daejeon, and an E-mart mall, Seoul.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2015-09
Language
English
Article Type
Article
Citation

ICT EXPRESS, v.1, no.2, pp.82 - 85

ISSN
2405-9595
DOI
10.1016/j.icte.2015.09.008
URI
http://hdl.handle.net/10203/209860
Appears in Collection
CS-Journal Papers(저널논문)
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