This framework presents GES in linear observed systems by optimizing a Kalman-like observer for navigation problems.
Linear observed systems on groups encode the geometry of a variety of practical state estimation problems. In this paper, we propose a unified 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 powerfully enables a system immersion of the original system into a linear time-varying system. Leveraging the immersion, an observer is constructed by first designing a Kalman-like observer for the immersed system and then reconstructing the group-valued state via optimization. Under a rank condition, global exponential stability (GES) is achieved provided 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. Two non-trivial examples are provided to illustrate implementation details.
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Liu et al. (2025) studied this question.
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