%0 Journal Article
%T Central difference Kalman smoother
中心差分卡尔曼平滑器
%A WANG Xiao-xu
%A PAN Quan
%A CHENG Yong-mei
%A ZHAO Chun-hui
%A YANG Feng
%A
王小旭
%A 潘泉
%A 程咏梅
%A 赵春晖
%A 杨峰
%J 控制理论与应用
%D 2012
%I
%X A central difference Kalman smoother (CDKS) is designed to solve the nonlinear state-smoothing problem for a class of nonlinear discrete-time systems. Optimal smoothing recursive formulas for estimating nonlinear system states are derived on the basis of minimum mean-square-error estimation; and the central difference transformation is used to calculate the posterior mean and covariance of nonlinear states. Compared with the standard central difference Kalman filter (CDKF), the proposed CDKS effectively improves the estimation precision of the nonlinear system states, and extends the applications of the central difference transformation. Simulations example shows the feasibility and effectiveness of the proposed smoother.
%K nonlinear discrete-time systems
%K central difference Kalman smoother
%K minimum mean square error estimation
%K central difference transformation
非线性离散系统
%K 中心差分卡尔曼平滑器
%K 最小方差估计
%K 中心差分变换
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=3E18639A9B66198E2E532D1B6B873A31&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=38B194292C032A66&sid=3E3EF0DB5E6F2DA9&eid=4C2B9916B58305BE&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0