Hidden Markov model-based 3D path-matching using raytracing-generated Wi-Fi models

We propose an efficient approach to probabilistic 3D indoor path-matching and localization based on Wi-Fi-signal measurements using Hidden Markov Model-based (HMM) algorithms. Given a 3D model of the building, we derive high-resolution emission probabilities and transition probabilities from raytrac...

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Bibliographic Details
Published in2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN) pp. 1 - 10
Main Authors Viol, N., Link, J. A. B., Wirtz, H., Rothe, D., Wehrle, K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2012
Subjects
Accuracy
Computational modeling
Hidden Markov models
IEEE 802.11 Standards
Radio propagation
Signal resolution
Solid modeling
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Summary:We propose an efficient approach to probabilistic 3D indoor path-matching and localization based on Wi-Fi-signal measurements using Hidden Markov Model-based (HMM) algorithms. Given a 3D model of the building, we derive high-resolution emission probabilities and transition probabilities from raytracing-generated Wi-Fi signal propagations. Therefore we use both the generated signal-strength values and the geometric information of the 3D model. Based on the emission and transition probabilities and a sequence of Wi-Fi signal measurements provided by the client, the HMM-based algorithm computes the most probable path through the building.
ISBN:1467319554
9781467319553
DOI:10.1109/IPIN.2012.6418873