A Hidden Markov Model for Pedestrian Navigation
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
Abstract
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.
Editors with CRIS profile
Jochen Seitz
Lehrstuhl für Informationstechnik mit dem Schwerpunkt Kommunikationselektronik (Stiftungslehrstuhl)
Jörn Thielecke
Professur für Informationstechnik (Schwerpunkt Ortsbestimmung und Navigation)
Involved external institutions
Germany (DE)How to cite
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.
BibTeX: Download