SINS/CNS integrated navigation solution using adaptive unscented Kalman filtering
Strapdown inertial navigation system (SINS) integrated with celestial navigation system (CNS) yields reliable mission capability and enhanced navigational accuracy for spacecrafts.A novel innovation-based adaptive estimation unscented Kalman filter (UKF) to solve the degradation performance caused by CNS unstable measurement disturbances in the SINS and CNS hybrid system is presented in this paper.The proposed adaptive unscented Kalman filter (AUKF) is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gains.After having deduced the proposed AUKF algorithm theoretically in detail,the approach is tested in the SINS/CNS integrated navigation system.Numerical simulation results show that the adaptive unscented Kalman filter outperforms the extended Kalman filtering (EKF) and conventional UKF with higher accuracy and robustness.It is demonstrated that this proposed approach is a valid solution for the unknown changing measurement noise existing in the nonlinear filter.
adaptive filtering nonlinear filtering unscented Kalman filter integrated navigation system SINS/CNS integration.
Cong-shan Qu Hua-long Xu Ying Tan
Xian Research Institute of Hi-tech,Hongqing Town,Xian,710025,China
国际会议
International Conference on Modelling,Identification and Control(模拟、鉴定、控制国际会议)
上海
英文
2008-06-29（万方平台首次上网日期，不代表论文的发表时间）