Title :
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
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;
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
DOI :
10.1109/ISSCAA.2008.4776364
