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GNSS trajectory anomaly detection using similarity comparison methods for pedestrian navigation

Peltola, Pekka; Xiao, Jialin; Moore, Terry; Jiménez, Antonio; Seco, Fernando

Authors

Pekka Peltola

Jialin Xiao isxjx1@nottingham.ac.uk

Terry Moore

Antonio Jiménez

Fernando Seco



Abstract

The urban setting is a challenging environment for GNSS receivers. Multipath and other anomalies typically increase the positioning error of the receiver. Moreover, the error estimate of the position is often unreliable. In this study, we detect GNSS trajectory anomalies by using similarity comparison methods between a pedestrian dead reckoning trajectory, recorded using a foot-mounted inertial measurement unit, and the corresponding GNSS trajectory. During a normal walk, the foot-mounted inertial dead reckoning setup is trustworthy up to a few tens of meters. Thus, the differing GNSS trajectory can be detected using form similarity comparison methods. Of the eight tested methods, the Hausdorff distance (HD) and the accumulated distance difference (ADD) give slightly more consistent detection results compared to the rest.

Journal Article Type Article
Publication Date Sep 19, 2018
Journal Sensors
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 18
Issue 9
Article Number 3165
Pages 3165
APA6 Citation Peltola, P., Xiao, J., Moore, T., Jiménez, A., & Seco, F. (2018). GNSS trajectory anomaly detection using similarity comparison methods for pedestrian navigation. Sensors, 18(9), doi:10.3390/s18093165
DOI https://doi.org/10.3390/s18093165
Keywords Electrical and Electronic Engineering; Analytical Chemistry; Atomic and Molecular Physics, and Optics; Biochemistry
Publisher URL http://www.mdpi.com/1424-8220/18/9/3165

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