Continuous-time filtering in Lie groups: estimation via the Fr\'echet mean of solutions to stochastic differential equations
Abstract
We compute the Fr\'echet mean Et of the solution Xt to a continuous-time stochastic differential equation in a Lie group. It provides an estimator with minimal variance of Xt. We use it in the context of Kalman filtering and more precisely to infer rotation matrices. In this paper, we focus on the prediction step between two consecutive observations. Compared to state-of-the-art approaches, our assumptions on the model are minimal.
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