Gaussian sum filtering based on uniformly Random Design with application to terrain navigation
Yanhong Zhang, Dong Liu, Guangbin Liu, Fei Cao · 2011
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.