Stability of the UKF for Nonlinear Stochastic Systems with Correlated Noises
The modified Unscented Kalman Filter (UKF) for nonlinear stochastic systems with correlated noises is presented. The modified UKF consists of the prediction equations and the measurement equations, and holds the sigma points chosen by Unscented Transformation (UT). The stability performance of the modified UKF is investigated. It is proved that under certain conditions, the estimation error of the UKF remains bounded. The influence of the noise covariance matrix on the UKF behavior is analyzed by introducing an extra positive definite matrix in the noise covariance matrix. It is shown that if the extra matrix is selected properly, the performance of the modified UKF may be improved significantly. The results are verified by using Matlab simulations on two numerical example systems.
Jiahe Xu Xiuping Zheng Xiaolong Qian Yuanwei Jing
Information Science and Engineering Northeastern University Shenyang, Liaoning,110004 P.R.China Information Science and Engineering Northeastern University Shenyang, Liaoning, 110004 P.R.China
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）