Road vehicle state estimation using low-cost GPS/INS
Date
2011-08-01T00:00:00Z
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Publisher
Elsevier Science B.V., Amsterdam
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Type
Article
ISSN
0888-3270
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Free to read from
Citation
Leung KT, Whidborne JF, Purdy D, Barber P. (2011) Road vehicle state estimation using low-cost GPS/INS. Mechanical Systems and Signal Processing, Volume 25, Issue 6, August 2011, pp. 1988-2004
Abstract
Assuming known vehicle parameters, this paper proposes an innovative integrated Kalman filter (IKF) scheme to estimate vehicle dynamics, in particular the sideslip, the heading and the longitudinal velocity. The IKF is compared with the 2DoF linear bicycle model, the triple Kalman filter (KF) and a model-based KF (MKF) in a simulation environment. Simulation results show that the proposed IKF is superior to other KF designs (both Kinematic KF and MKF) on state estimation when tyre characteristics are within the linear region (i.e. manoeuvres below 55 kph).
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NOTICE: this is the author’s version of a work that was accepted for publication in Mechanical Systems and Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Mechanical Systems and Signal Processing, VOL 25, ISSUE 6, (2011) DOI: 10.1016/j.ymssp.2010.08.003