摘要
阐述了标称状态的线性化方法和扩展的卡尔曼滤波公式及迭代卡尔曼滤波,探讨了非线性动态滤波的近似处理方法,围绕标称状态将非线性模型进行线性化,将标准的卡尔曼滤波扩展到非线性模型,得到扩展的卡尔曼滤波公式,研究了迭代滤波计算方法。扩展的卡尔曼滤波方法已经有效地用于非线性模型。
The algorithm of iterative Kalman filter is presented based on the general Kalman filter and the extended Kalman filter. The approximate processing methods for nonlinear dynamic filters are discussed. The nonlinear model is linearized for the nominal state system and the general Kalman filters is extended to the nonlinear model. Finally the extended Kalman filter formula is derived and the iterative algorithm is established. The extended Kalman filtering method has been effectively used in the nonlinear model.
出处
《数据采集与处理》
CSCD
北大核心
2007年第4期431-434,共4页
Journal of Data Acquisition and Processing
基金
江苏省高校自然科学基金(04KJB170140)资助项目
关键词
卡尔曼滤波
非线性模型
动态滤波
迭代法
Kalman filter
nonlinear model
dynamic filter
iterative algorithm
