Three examples of the stability properties of the invariant extended Kalman filter

被引:23
作者
Barrau, A. [1 ]
Bonnabel, S. [2 ]
机构
[1] SAFRAN TECH, Grp Safran, Rue Jeunes Bois Chateaufort, F-78772 Magny Les Hameaux, France
[2] PSL Reasearch Univ, Ctr Robot, MINES Paris Tech, 60 Bd St Michel, F-75006 Paris, France
关键词
Estimation; Kalman filtering; nonlinear systems; Lie groups; navigation;
D O I
10.1016/j.ifacol.2017.08.061
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the aerospace industry the (multiplicative) extended Kalman filter (EKF) is the most common method for sensor fusion for guidance and navigation. However, from a theoretical point of view, the EKF has been shown to possess local convergence properties only under restrictive assumptions. In a recent paper, we proved a slight variant of the EKF, namely the invariant extended Kalman filter (IEKF), when used as a nonlinear observer, possesses local convergence properties under the same assumptions as those of the linear case, for a class of systems defined on Lie groups. This is especially interesting as the IEKF also retains all the desirable features of the standard EKF, especially its relevant tuning in the presence of noises. In the present paper we provide three examples of engineering interest where the theory is shown to apply, yielding three EKF-like algorithms with guaranteed local convergence properties. Beyond those contributions, the present article is sufficiently accessible to help the practitioner understand through concrete examples the general IEKF theory, and to provide him with guidelines for the design of IEKFs. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:431 / 437
页数:7
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