A new algorithm for satellite autonomous navigation based on information fusion

Author

Ying, Miao ; Zhaowei, Sun

Author_Institution

Res. Centre of Satellite Technol., Harbin Inst. of Technol., Harbin

fYear

2008

fDate

10-12 Dec. 2008

Firstpage

1

Lastpage

5

Abstract

In this paper, an effective and reliable algorithm for satellite autonomous navigation is proposed. In order to speed the convergence of navigation errors, the autonomous navigation algorithm is designed with information fusion of magnetometer and radar altimeter. In this algorithm, a modified UKF is applied to perform the information fusion. Compare with conventional UKF and EKF, the modified UKF simplified the estimating process, improves the efficiency. Through the combined filter, a global optimum estimated state value is obtained. Simulation results show this information fusion navigation algorithm is steady and converge fast.

Keywords

Kalman filters; magnetometers; nonlinear filters; radar altimetry; satellite navigation; sensor fusion; EKF; UKF; extended Kalman filter; information fusion; magnetometer; radar altimeter; satellite autonomous navigation; unscented Kalman filter; Convergence; Coordinate measuring machines; Extraterrestrial measurements; Filters; Geomagnetism; Magnetic field measurement; Magnetometers; Satellite navigation systems; Spaceborne radar; Velocity measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Control in Aerospace and Astronautics, 2008. ISSCAA 2008. 2nd International Symposium on

Conference_Location

Shenzhen

Print_ISBN

978-1-4244-3908-9

Electronic_ISBN

978-1-4244-2386-6

Type

conf

DOI

10.1109/ISSCAA.2008.4776364

Filename

4776364