A Novel Finite State Machine Based Step Detection Technique for Pedestrian Navigation Systems. Ruppelt, J & Kronenwett, N abstract bibtex — In this paper we present a novel finite state machine based step detection technique for precise personal navigation so-lutions with a foot-mounted inertial measurement unit (IMU). Generally, step detection methods are used to improve the naviga-tion solution by applying Zero Velocity Updates (ZUPTs) in the navigation filter. All step detection techniques distort the naviga-tion solution if ZUPTs are utilized at wrong times. Our approach based on a finite state machine is able to detect different stances of the foot with high accuracy. Therefore, Zero Velocity Updates can be applied in time and positively affect the precision of the naviga-tion solution. The functionality of the step detection module in combination with a constraint, stochastic cloning (SC) Kalman fil-ter are analyzed with real sensor data recorded with our pedes-trian navigation system. Even with ultra-low cost inertial sensors, this new approach can clearly increase the accuracy of pedestrian navigation systems compared to state-of-the-art approaches.
@article{ruppeltNovelFiniteState2015,
title = {A {{Novel Finite State Machine Based Step Detection Technique}} for {{Pedestrian Navigation Systems}}},
abstract = {— In this paper we present a novel finite state machine based step detection technique for precise personal navigation so-lutions with a foot-mounted inertial measurement unit (IMU). Generally, step detection methods are used to improve the naviga-tion solution by applying Zero Velocity Updates (ZUPTs) in the navigation filter. All step detection techniques distort the naviga-tion solution if ZUPTs are utilized at wrong times. Our approach based on a finite state machine is able to detect different stances of the foot with high accuracy. Therefore, Zero Velocity Updates can be applied in time and positively affect the precision of the naviga-tion solution. The functionality of the step detection module in combination with a constraint, stochastic cloning (SC) Kalman fil-ter are analyzed with real sensor data recorded with our pedes-trian navigation system. Even with ultra-low cost inertial sensors, this new approach can clearly increase the accuracy of pedestrian navigation systems compared to state-of-the-art approaches.},
issue = {October},
date = {2015},
pages = {13--16},
keywords = {navigation,can be corrupted due,finite state machine,for that reason,indoor,indoor navigation,navigation systems need other,navigation techniques to reduce,pedestrian,step detection,to multipath effects},
author = {Ruppelt, J and Kronenwett, N},
file = {/home/dimitri/Nextcloud/Zotero/storage/YBXN3UHI/Ruppelt, Kronenwett, Trommer - 2015 - A Novel Finite State Machine Based Step Detection Technique for Pedestrian Navigation Systems.pdf}
}
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