Gaussian particle filtering in high-dimensional systems

In Gaussian particle filtering the distributions of interest are approximated by Gaussians or mixtures of Gaussians. In this paper, we present an approach for using Gaussian particle filtering in high dimensional systems. The approach is based on breaking the high-dimensional systems into smaller-dimensional systems (subsystems) and applying Gaussian particle filtering in each of the subsystems. The subsystems exchange information with other (relevant) subsystems so that the operations of the Gaussian particle filtering in the subsystems can be carried out unimpeded. We demonstrate the proposed approach by computer simulations.