Title :
Terrain Aided Navigation Algorithm Using Gaussian Sum Particle Filter
Author :
Liao, Wei ; Weng, Lubin ; Tai, Xianqing
Author_Institution :
Inst. of Autom., Chinese Acad. of Sci., Beijing, China
Abstract :
In order to improve the positioning accuracy of the Terrain Aided Navigation (TAN) system and the applicability of the aided navigation algorithm to terrain matching problem, a novel framework based on Gaussian sum particle filter(GSPF) is proposed. With the establishment of the nonlinear non-Gaussian navigation system model, the GSPF algorithm is used to rectify the position and the velocity errors of the Inertial Navigation System (INS) through matching the measured elevation data and the standard terrain elevation map. Compared with the square root unscented Kalman filter(SRUKF) and the basic particle filter(PF) used in the TAN system, the simulation experiments show better results in root mean square error(RMSE) and circular error probable(CEP).
Keywords :
Gaussian processes; Kalman filters; digital elevation models; inertial navigation; mean square error methods; particle filtering (numerical methods); terrain mapping; GSPF algorithm; Guassian sum particle filter; TAN system; circular error probablity; inertial navigation system; nonlinear nonGaussian navigation system; root mean square error; square root unscented Kalman filter; standard terrain elevation map; terrain aided navigation algorithm; terrain matching problem; velocity error; Aerodynamics; Filtering algorithms; Kalman filters; Matched filters; Navigation; Particle filters;
Conference_Titel :
Pattern Recognition (CCPR), 2010 Chinese Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-7209-3
Electronic_ISBN :
978-1-4244-7210-9
DOI :
10.1109/CCPR.2010.5659307
