Hidden Markov Model-based Pedestrian Navigation System using MEMS Inertial Sensors.
In: Measurement Science Review, Jg. 15 (2015-02-01), Heft 1, S. 35-43
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Zugriff:
In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemented, where the zero-velocity detection is abstracted into a hidden Markov model with 4 states and 15 observations. Moreover, an observations extraction algorithm has been developed to extract observations from sensor outputs; sample sets are used to train and optimize the model parameters by the Baum-Welch algorithm. Finally, a navigation system is developed, and the performance of the pedestrian navigation system is evaluated using indoor and outdoor field tests, and the results show that position error is less than 3% of total distance travelled. [ABSTRACT FROM AUTHOR]
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Titel: |
Hidden Markov Model-based Pedestrian Navigation System using MEMS Inertial Sensors.
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Autor/in / Beteiligte Person: | Zhang, Yingjun ; Liu, Wen ; Yang, Xuefeng ; Xing, Shengwei |
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Zeitschrift: | Measurement Science Review, Jg. 15 (2015-02-01), Heft 1, S. 35-43 |
Veröffentlichung: | 2015 |
Medientyp: | academicJournal |
ISSN: | 1335-8871 (print) |
DOI: | 10.1515/msr-2015-0006 |
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