%0 Journal Article
%T Robust Kalman filter design for unknown noise covariance<br>噪声统计特性未知时的鲁棒卡尔曼滤波算法设计
%A WANG Jian-wen
%A SHUI Hai-tao
%A LI Xun
%A ZHANG Hui
%A MA Hong-xu
%A <br>王建文
%A 税海涛
%A 李迅
%A 张辉
%A 马宏绪
%J 控制理论与应用
%D 2011
%I 
%X This paper is concerned with the problem of a robust Kalman filter(RKF) design when noise covariance is unknown in stochastic linear systems. A novel design criterion for RKFs is proposed, and its rationality is analyzed. Based on the criterion, the design of a RKF is transformed to solving a linear matrix inequality(LMI). The results are validated by simulations.
%K stochastic linear system
%K robust Kalman filter
%K design criterion
%K linear matrix inequality<br>随机线性系统
%K 鲁棒卡尔曼滤波算法
%K 设计条件
%K 线性矩阵不等式
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=C52548B92BC6C5BBB37EB1A9A3662B7E&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=94C357A881DFC066&sid=99A964928ADB4E67&eid=780091CB32840698&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=14