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The Geometry of Navigation Problems
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DOI：10.1109/TAC.2022.3144328.png)
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摘要
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While many works exploiting an existing Lie group structure have been proposed for state estimation, in particular the invariant extended Kalman filter (IEKF), few papers address the construction of a group structure that allows casting a given system into the framework of invariant filtering. In this article, we introduce a large class of systems encompassing most problems involving a navigating vehicle encountered in practice. For those systems we introduce a novel methodology that systematically provides a group structure for the state space, including vectors of the body frame such as biases. We use it to derive observers having properties akin to those of linear observers or filters. The proposed unifying and versatile framework encompasses all systems, where IEKF has proved successful, improves state-of-the art imperfect IEKF for inertial navigation with sensor biases, and allows addressing novel examples, like GNSS antenna lever arm estimation.
Keyword:
Observers
Simultaneous localization and mapping
Kalman filters
Vehicle dynamics
Inertial navigation
Convergence
Manipulators
Aircraft navigation
autonomous vehicles
geometry
nonlinear filters
observers
state estimation
期刊
IF:
7
论文数:
1.3W
被引数:
6.7W
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