Global Observer Design for a Class of Linear Observed Systems on Groups
This work addresses state estimation challenges in navigation and robotics by providing a novel observer framework for non-Euclidean systems, though it is incremental as it builds on existing group-based methods.
The paper tackles the problem of designing globally stable observers for linear observed systems on Lie groups by embedding them into linear time-varying systems and using a Kalman-like approach with optimization for state reconstruction. It achieves global exponential stability under specific conditions and applies the theory to navigation problems, with simulations demonstrating implementation.
Linear observed systems on groups encode the geometry of a variety of practical state estimation problems. In this paper, we propose an observer framework for a class of linear observed systems by restricting a bi-invariant system on a Lie group to its normal subgroup. This structural property enables a system embedding of the original system into a linear time-varying system. An observer is constructed by first designing a Kalman-like observer for the embedded system and then reconstructing the group-valued state via optimization. Under an extrinsic observability rank condition, global exponential stability (GES) is achieved provided that one global optimum of the reconstruction optimization is found, reflecting the topological difficulties inherent to the non-Euclidean state space. Semi-global stability is guaranteed when input biases are jointly estimated. The theory is applied to the GES observer design for two-frame systems, capable of modeling a family of navigation problems. Simulations are provided to illustrate the implementation details.