Title :
Gaussian sum filtering based on uniformly Random Design with application to terrain navigation
Author :
Zhang, Yanhong ; Liu, Dong ; Liu, Guangbin ; Cao, Fei
Author_Institution :
Dept. of Autom., Xi´´an Res. Inst. Of High-Tech, Xi´´an, China
Abstract :
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.
Keywords :
Gaussian processes; expectation-maximisation algorithm; nonlinear filters; 2D terrain navigation; Gaussian sum filtering; finite mixture models; nonlinear non-Gaussian dynamic system filtering; uniformly random design method; weighted expectation maximization algorithm; Aircraft navigation; Approximation methods; Filtering algorithms; Kalman filters; Monte Carlo methods; Vectors; Gaussian Sum Filtering; Nonlinear Filtering; Terrain Navigation; UGSF;
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
DOI :
10.1109/CISP.2011.6100670
