An Adaptive Unscented Kalman Filter Based Spacecraft Autonomous Navigation Algorithm
Yong Li · Aerospace Control and Application · 2009
A new approach called as adaptive unscented Kalman filter(AUKF) for nonlinear filtering systems is presented in this paper.This method combines nonlinear Sage-Husa noise statistics estimator with unscented Kalman filter(UKF).Then AUKF is applied to the spacecraft autonomous navigation.The computer simulation results demonstrate that the navigation accuracy using AUKF is much better than using EKF.And a new algorithm to improve measurement bias estimate precision by using periodic information of the measurement bias is proposed.The autonomous navigation system simulation results show that with a little more computing time the improved AUKF using the new measurement bias estimate algorithm is more accurate than AUKF.