自动化学报2013，Vol.39Issue(1)：43-52,10.DOI:10.3724/SP.J.1004.2013.00043
在不准确方差下带随机系数矩阵的卡尔曼滤波稳定性
L2-stability of Discrete-time Kalman Filter with Random Coefficients under Incorrect Covariance
摘要
Abstract
This paper studies the L2-stability of Kalman filter for discrete-time linear stochastic systems. Two main features, i.e., random coefficient matrices and incorrect covariances of process noise, measurement noise and initial value, are emphasized. Under suitable conditions, including boundedness of coefficient matrices, conditional observability and boundedness of initial error and noises, L2-stability of Kalman filter is achieved. The equivalence between Kalman filter and state-space least squares algorithm is established. Based on this equivalence, instability of state estimation error by state-space least squares is also obtained. A numerical example is given to demonstrate the effectiveness of Kalman filtering algorithm.关键词
状态估计/稳定性/卡尔曼滤波/状态空间最小二乘Key words
State estimation/ stability/ Kalman filter/ state-space least squares引用本文复制引用
周振威,方海涛..在不准确方差下带随机系数矩阵的卡尔曼滤波稳定性[J].自动化学报,2013,39(1):43-52,10.基金项目
国家自然科学基金(61174143)资助 （61174143）
