Robust Adaptive Unscented Kalman Filter for Spacecraft Attitude Estimation Using Quaternion Measurements
Publication: Journal of Aerospace Engineering
Volume 30, Issue 4
Abstract
A robust unscented Kalman filter based on a multiplicative quaternion-error approach is proposed for high-precision spacecraft attitude estimation using quaternion measurements under measurement faults. The global attitude parameterization is given by a quaternion, whereas the local attitude error is defined using a generalized three-dimensional attitude representation. To guarantee quaternion normalization in the filter, the unscented Kalman filter is formulated with a multiplicative quaternion-error approach derived from the local attitude error. A standard unscented Kalman filter provides sufficiently good estimation results even for initial large error conditions. However, in the case of measurement sensor malfunctions, the unscented Kalman filter fails in providing the required estimation accuracy and may even collapse over time. The proposed algorithm uses a statistical function including measurement residuals to detect measurement faults and then uses an adaptation scheme based on a multiple scale factor so that the filter may stand robust against faulty measurements. The proposed algorithm is demonstrated for attitude estimation of a spacecraft using quaternion measurements in three measurement fault cases. The estimation performance of the proposed algorithm is also compared with those of the standard extended Kalman filter and unscented Kalman filter under the same simulation conditions.
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Published In
Journal of Aerospace Engineering
Volume 30 • Issue 4 • July 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jul 5, 2016
Accepted: Oct 17, 2016
Published ahead of print: Jan 31, 2017
Published online: Feb 1, 2017
Published in print: Jul 1, 2017
Discussion open until: Jul 1, 2017
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