Improving Inertial Navigation Systems with Pedestrian Locomotion Classifiers

Courtney Ngo, Solomon See, Roberto Legaspi

Abstract

Researches on inertial navigation systems (INS) have formulated complex step detection algorithms and stride length estimations. But for current systems to work, INSs have to correctly identify negative pedestrian locomotion. Negative pedestrian locomotion are movements that a user can naturally make without any real position displacement, but has sensor signals that might be misidentified as steps. As the INS’s modules have a cascading nature, it is important that these false movements are identified beforehand. This research aims to provide a solution by studying patterns exhibited by positive and negative pedestrian locomotion when sensors are placed on a user’s front pocket. A model was then built to classify negative from positive pedestrian locomotion, and to improve the INS’s accuracy overall.

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Paper Citation


in Harvard Style

Ngo C., See S. and Legaspi R. (2015). Improving Inertial Navigation Systems with Pedestrian Locomotion Classifiers . In Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS, ISBN 978-989-758-084-0, pages 202-208. DOI: 10.5220/0005242802020208


in Bibtex Style

@conference{peccs15,
author={Courtney Ngo and Solomon See and Roberto Legaspi},
title={Improving Inertial Navigation Systems with Pedestrian Locomotion Classifiers},
booktitle={Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,},
year={2015},
pages={202-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005242802020208},
isbn={978-989-758-084-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,
TI - Improving Inertial Navigation Systems with Pedestrian Locomotion Classifiers
SN - 978-989-758-084-0
AU - Ngo C.
AU - See S.
AU - Legaspi R.
PY - 2015
SP - 202
EP - 208
DO - 10.5220/0005242802020208