Seitz J, Vaupel T, Meyer S, Gutierrez J, Thielecke J (2010)
Publication Type: Edited Volume
Publication year: 2010
Publisher: IEEE Xplore
Series: A Hidden Markov Model for Pedestrian Navigation
City/Town: online
Book Volume: 1
Pages Range: 120-127
Edition: 1
ISBN: 978-1-4244-7158-4
URI: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5650501
DOI: 10.1109/WPNC.2010.5650501
We present an algorithm for pedestrian navigation optimized for smart mobile platforms using the present low-cost sensors and the limited processing power. The algorithm is based on a Hidden Markov Model that combines Wi-Fi positioning and dead reckoning. The hidden states are the positions of the Wi-Fi fingerprints in the database. The state transition includes dead reckoning based on step length estimation from acceleration measurements and compass heading calculated from magnetic field measurements. In the measurement update a database correlation of the actual Wi-Fi signal strength measurements with the stored values in the fingerprints has been performed. In simulations and tests we demonstrate that in this way ambiguities common in Wi-Fi positioning can be reduced. Therefor, higher accuracy and robustness can be achieved. © 2010 IEEE.
APA:
Seitz, J., Vaupel, T., Meyer, S., Gutierrez, J., & Thielecke, J. (Eds.) (2010). A Hidden Markov Model for Pedestrian Navigation. online: IEEE Xplore.
MLA:
Seitz, Jochen, et al, eds. A Hidden Markov Model for Pedestrian Navigation. online: IEEE Xplore, 2010.
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