Title :
Improved UKF Algorithm for Divergence-Suppression and Its Application to Orbit Determination
Author :
Xue-jiao Guo ; Hai-yin Zhou
Author_Institution :
Dept. of Math. & Syst. Sci., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
The Unscented Kalman Filter (UKF) improved the linearization of system, but it do follow the Kalman Filter (KF) framework, the instability and the divergence of filter does not avoided while the increase of the measurement time in the practice. The reasons of the filter instability are discussed and two novel improved algorithms for divergence-suppression are presented in this paper. Moreover simulations are conducted using the satellites orbit determination, and the results are compared with those obtained by normal UKF to illuminate the major reasons of filter instability and demonstrate its effctiveness and advantages over the previous methods.
Keywords :
Kalman filters; artificial satellites; divergence-suppression; filter instability; improved UKF algorithm; satellites orbit determination; unscented Kalman filter framework; Covariance matrix; Extraterrestrial measurements; Filtering algorithms; Gain measurement; Kalman filters; Time measurement; Divergence; Improved UKF; Satellite Orbit Determination; Suppression; UKF; UT;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on
Print_ISBN :
978-1-4244-8333-4
DOI :
10.1109/ISDEA.2010.321