Gaussian sum filtering based on uniformly Random Design with application to terrain navigation

In this paper, densities are approximated as finite mixture models as is done in the Gaussian sum filter (GSF). A novel GSF (UGSF) for filtering nonlinear non-Gaussian dynamic system is proposed which updates the means and covariances of the mixands using uniformly Random Design(URD) method. To keep the number of the mixands constant, a method of weighted Expectation Maximization (WEM) algorithm is used. The novel filter is results in 2-D terrain navigation, the simulation results also illustrates the performance outgoes GMSPPE and UKF.