Sigma-Point Kalman Filters for GPS Based Position Estimation

Author

Bo, Tang ; Pingyuan, Cui ; Yangzhou, Chen

Author_Institution

Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol.

fYear

0

fDate

0-0 0

Firstpage

213

Lastpage

217

Abstract

Stand-alone GPS based position estimation problem using GPS raw data, pseudo-range and Doppler shifts measurements are the concept of fusing noisy observations. A family of improved derivative nonlinear Kalman filters called sigma point Kalman filter (SPKF) are applied to a nonlinear model of GPS based position estimation in this paper. Simulations are made to compare the filter with the traditional iterative least square (ILS) method and extended Kalman filter (EKF) method, results indicate that under same conditions, SPKF has higher filtering accuracy and more stable estimation performance

Keywords

Doppler measurement; Doppler shift; Global Positioning System; Kalman filters; nonlinear filters; Doppler shift measurement; GPS based position estimation; Global Positioning System; SPKF; nonlinear Kalman filters; sigma-point Kalman filter; Control engineering; Doppler shift; Filtering; Global Positioning System; Iterative methods; Least squares approximation; Nonlinear equations; Nonlinear filters; Position measurement; Satellites; Estimation; GPS; Kalman Filter; Sigma Point;

fLanguage

English

Publisher

ieee

Conference_Titel

Information, Communications and Signal Processing, 2005 Fifth International Conference on

Conference_Location

Bangkok

Print_ISBN

0-7803-9283-3

Type

conf

DOI

10.1109/ICICS.2005.1689037

Filename

1689037