控制理论与应用2016，Vol.33Issue(7)：973-979,7.DOI:10.7641/CTA.2016.50620
带丢失观测和不确定噪声方差系统改进的鲁棒协方差交叉融合稳态Kalman滤波器
Modified robust covariance intersection fusion steady-state Kalman filter for systems with missing measurements and uncertain noise variances
摘要
Abstract
For the linear time-invariant multisensor system with missing measurements and uncertain noise variances, by introducing the fictitious noises, the original system can be converted into one with only uncertain noise variances. According to the minimax robust estimation principle, using the Lyapunov equation approach, the local robust steady-state Kalman filters and the minimal upper bounds of their actual variances are presented, and a modified robust covariance intersection (CI) fusion steady-state Kalman filter and the minimal upper bound of its actual variances are presented using the conservative cross-covariances of the local filtering errors. The robustness of the robust local and fused filters is proved, and it is proved that the robust accuracy of the modified CI fuser is higher than that of the original CI fuser, and higher than that of each local filter. A simulation example verifies correctness and effectiveness of the proposed results.关键词
多传感器系统/不确定噪声方差/丢失观测/协方差交叉(CI)融合/极大极小鲁棒Kalman滤波器/Lyapu-nov方程方法Key words
multisensor system/uncertain noise variance/missing measurements/covariance intersection (CI) fusion/minimax robust Kalman filter/Lyapunov equation approach分类
数理科学引用本文复制引用
王雪梅,刘文强,邓自立..带丢失观测和不确定噪声方差系统改进的鲁棒协方差交叉融合稳态Kalman滤波器[J].控制理论与应用,2016,33(7):973-979,7.基金项目
国家自然科学基金项目(60874063,60374026),黑龙江大学研究生创新科研项目(YJSCX2015-002HLJU)资助 （60874063,60374026）
