An adaptive hybrid filter for practical WiFi-based positioning systems

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, an...

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Bibliographic Details
Published inICT express Vol. 1; no. 2; pp. 82 - 85
Main Authors Park, Namjun, Jung, Sukhoon, Han, Dongsoo
Format Journal Article
LanguageEnglish
Published Elsevier 01.09.2015
Subjects
Adaptive hybrid filter
Indoor positioning system
Kalman filter
Particle filter
WiFi fingerprint
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Summary: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.
ISSN:2405-9595
2405-9595
DOI:10.1016/j.icte.2015.09.008