Robust Estimation of UAV Dynamics in the Presence of Measurement Faults
Publication: Journal of Aerospace Engineering
Volume 25, Issue 1
Abstract
This study introduces a robust Kalman filter (RKF) with a filter-gain correction for cases of measurement malfunctions. Using defined variables called measurement-noise scale factors, the faulty measurements are taken into consideration with a small weight and the estimations are corrected without affecting the characteristics of the accurate ones. In this study, RKF algorithms with single and multiple scale factors are proposed and applied for the state estimation process of an unmanned aerial vehicle (UAV) platform. The results of these algorithms are compared for different types of measurement faults, and recommendations for their utilization are given.
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Information
Published In
Journal of Aerospace Engineering
Volume 25 • Issue 1 • January 2012
Pages: 80 - 89
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Feb 10, 2010
Accepted: Nov 19, 2010
Published online: Dec 4, 2010
Published in print: Jan 1, 2012
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