Equivalence of Left- and Right-Invariant Extended Kalman Filters on Matrix Lie Groups

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Auteurs principaux: Maurer, Finn G., Basso, Erlend A., Schmidt-Didlaukies, Henrik M., Bryne, Torleiv H.
Format: Preprint
Publié: 2025
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author Maurer, Finn G.
Basso, Erlend A.
Schmidt-Didlaukies, Henrik M.
Bryne, Torleiv H.
author_facet Maurer, Finn G.
Basso, Erlend A.
Schmidt-Didlaukies, Henrik M.
Bryne, Torleiv H.
contents This paper derives the extended Kalman filter (EKF) for continuous-time systems on matrix Lie groups observed through discrete-time measurements. By modeling the system noise on the Lie algebra and adopting a Stratonovich interpretation for the stochastic differential equation (SDE), we ensure that solutions remain on the manifold. The derivation of the filter follows classical EKF principles, naturally integrating a necessary full-order covariance reset post-measurement update. A key contribution is proving that this full-order covariance reset guarantees that the Lie-group-valued state estimate is invariant to whether a left- or right-invariant error definition is used in the EKF. Monte Carlo simulations of the aided inertial navigation problem validate the invariance property and confirm its absence when employing reduced-order covariance resets.
format Preprint
id arxiv_https___arxiv_org_abs_2506_01514
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Equivalence of Left- and Right-Invariant Extended Kalman Filters on Matrix Lie Groups
Maurer, Finn G.
Basso, Erlend A.
Schmidt-Didlaukies, Henrik M.
Bryne, Torleiv H.
Systems and Control
This paper derives the extended Kalman filter (EKF) for continuous-time systems on matrix Lie groups observed through discrete-time measurements. By modeling the system noise on the Lie algebra and adopting a Stratonovich interpretation for the stochastic differential equation (SDE), we ensure that solutions remain on the manifold. The derivation of the filter follows classical EKF principles, naturally integrating a necessary full-order covariance reset post-measurement update. A key contribution is proving that this full-order covariance reset guarantees that the Lie-group-valued state estimate is invariant to whether a left- or right-invariant error definition is used in the EKF. Monte Carlo simulations of the aided inertial navigation problem validate the invariance property and confirm its absence when employing reduced-order covariance resets.
title Equivalence of Left- and Right-Invariant Extended Kalman Filters on Matrix Lie Groups
topic Systems and Control
url https://arxiv.org/abs/2506.01514