GNSS trajectory anomaly detection using similarity comparison methods for pedestrian navigation

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

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.

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), Article 3165. https://doi.org/10.3390/s18093165

• Journal Article Type: Article
• Acceptance Date: Sep 14, 2018
• Online Publication Date: Sep 19, 2018
• Publication Date: Sep 19, 2018
• Deposit Date: Sep 20, 2018
• Publicly Available Date: Sep 20, 2018
• Journal: Sensors
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 18
• Issue: 9
• Article Number: 3165
• DOI: https://doi.org/10.3390/s18093165
• Keywords: Electrical and Electronic Engineering; Analytical Chemistry; Atomic and Molecular Physics, and Optics; Biochemistry
• Public URL: https://nottingham-repository.worktribe.com/output/1093298
• Publisher URL: http://www.mdpi.com/1424-8220/18/9/3165