A Hidden Markov Model for Urban Navigation Based on Fingerprinting and Pedestrian Dead Reckoning
Thielecke J, Gutiérrez Boronat J, Seitz J, Meyer S, Jahn J, Vaupel T (2010)
Publication Type: Edited Volume
Publication year: 2010
Publisher: IEEE Xplore
Series: A Hidden Markov Model for Urban Navigation Based on Fingerprinting and Pedestrian Dead Reckoning
City/Town: online
ISBN: 9780982443811
URI: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5712025&tag=1
Abstract
An algorithm for pedestrian navigation in indoor and urban canyon environments is presented. It considers platforms with low processing power and low-cost sensors. A combination of Wi-Fi positioning and dead reckoning, based on a Hidden Markov Model, is used. The positions of the Wi-Fi fingerprints in the database are used as hidden states. Dead reckoning is taken for state transition and a database correlation of the Wi-Fi signal strength measurements is performed in the measurement update. The dead reckoning consists of an accelerometer driven step length estimation and a magnetic field based heading calculation. Simulations and tests demonstrate that in this way ambiguities common in Wi-Fi positioning can be solved and outages can be bridged. Therefore, higher accuracy and robustness can be achieved.
Editors with CRIS profile
Jörn Thielecke
Professur für Informationstechnik (Schwerpunkt Ortsbestimmung und Navigation)
Jochen Seitz
Lehrstuhl für Informationstechnik mit dem Schwerpunkt Kommunikationselektronik (Stiftungslehrstuhl)
Involved external institutions
Germany (DE)How to cite
APA:
Thielecke, J., Gutiérrez Boronat, J., Seitz, J., Meyer, S., Jahn, J., & Vaupel, T. (Eds.) (2010). A Hidden Markov Model for Urban Navigation Based on Fingerprinting and Pedestrian Dead Reckoning. online: IEEE Xplore.
MLA:
Thielecke, Jörn, et al, eds. A Hidden Markov Model for Urban Navigation Based on Fingerprinting and Pedestrian Dead Reckoning. online: IEEE Xplore, 2010.
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