Open AccessExtended robust Kalman filter for attitude estimation
Author(s) -
Inoue Roberto Santos,
Terra Marco Henrique,
Cerri João Paulo
Publication year - 2016
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2015.0235
Subject(s) - control theory (sociology) , kalman filter , quaternion , invariant extended kalman filter , a priori and a posteriori , extended kalman filter , alpha beta filter , computer science , filter (signal processing) , fast kalman filter , inertial frame of reference , mathematics , artificial intelligence , computer vision , moving horizon estimation , control (management) , philosophy , physics , geometry , epistemology , quantum mechanics
In this study, the authors deal with inertial measurement units subject to uncertainties. They propose an extended robust Kalman filter (ERKF) in a predictor–corrector form to estimate a rigid body attitude. The filter is developed based on regularisation and penalisation whose approaches present the advantage of encompassing in a unified framework all state and output uncertain parameters of the system. The ERKF is tuned based on two degree of freedom which belong to a certain interval known a ‐ priori , useful for online applications. The attitude estimation system proposed takes into account a rigid body model formulated in terms of quaternions. Experimental results are presented based on a comparative study among the ERKF, the standard extended Kalman filter and an ℋ ∞ filter.