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

fYear

2010

fDate

21-23 Oct. 2010

Firstpage

1

Lastpage

5

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/CCPR.2010.5659307

Filename

5659307