Improving Inertial Navigation Systems with Pedestrian Locomotion Classifiers

Courtney Ngo; Solomon See; Roberto Legaspi

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Paper

Improving Inertial Navigation Systems with Pedestrian Locomotion Classifiers

Topics: Detection and Estimation

In Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems PECCS - Volume 1, 202-208, 2015 , ESEO, Angers, Loire Valley, France

Authors: Courtney Ngo ¹ ; Solomon See ¹ and Roberto Legaspi ²

Affiliations: ¹ De La Salle University-Manila, Philippines ; ² The Institute of Statistical Mathematics, Japan

Keyword(s): Machine Learning, Inertial Navigation System, Sensors.

Related Ontology Subjects/Areas/Topics: Detection and Estimation ; Digital Signal Processing ; Telecommunications

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 several formats:

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 - PECCS; ISBN 978-989-758-084-0; ISSN 2184-2817, SciTePress, pages 202-208. DOI: 10.5220/0005242802020208

@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 - PECCS},
year={2015},
pages={202-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005242802020208},
isbn={978-989-758-084-0},
issn={2184-2817},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - PECCS
TI - Improving Inertial Navigation Systems with Pedestrian Locomotion Classifiers
SN - 978-989-758-084-0
IS - 2184-2817
AU - Ngo, C.
AU - See, S.
AU - Legaspi, R.
PY - 2015
SP - 202
EP - 208
DO - 10.5220/0005242802020208
PB - SciTePress