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Sensors 2015, 15(9), 24269-24296; doi:10.3390/s150924269

An Enhanced Error Model for EKF-Based Tightly-Coupled Integration of GPS and Land Vehicle’s Motion Sensors

Electrical and Computer Engineering, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada
These authors contributed equally to this work.
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Author to whom correspondence should be addressed.
Academic Editor: Luis Javier Garcia Villalba
Received: 20 July 2015 / Revised: 9 September 2015 / Accepted: 11 September 2015 / Published: 22 September 2015
(This article belongs to the Special Issue Advances on Resources Management for Multi-Platform Infrastructures)
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Abstract

Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers’ measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer’s errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories’ data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance. View Full-Text
Keywords: inertial sensors; wheel rotation sensors; Global Positioning System; gyroscope; accelerometer; extended Kalman filter inertial sensors; wheel rotation sensors; Global Positioning System; gyroscope; accelerometer; extended Kalman filter
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Karamat, T.B.; Atia, M.M.; Noureldin, A. An Enhanced Error Model for EKF-Based Tightly-Coupled Integration of GPS and Land Vehicle’s Motion Sensors. Sensors 2015, 15, 24269-24296.

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