%0 Journal Article
%T Integrated navigation algorithm based on IMM-UKF<br>基于IMM-UKF的组合导航算法
%A ZANG Rong-chun
%A CUI Ping-yuan
%A CUI Hu-tao
%A JIN Yi
%A <br>臧荣春
%A 崔平远
%A 崔祜涛
%A 金艺
%J 控制理论与应用
%D 2007
%I 
%X A new unscented Kalman filter(UKF)based on interacting multiple model(IMM)is presented to solve the problem of nonlinear filtering and noise modeling.The uncertainty of the noise can be described by a set of switching models.In every model a UKF is running,and the UKF for nonlinear filtering can achieve accuracy at least to the second order.The output of the IMM-UKF is the weighted sum of a bank of parallel unscented Kalman filters.The self-adaptive filtering for different noises can be performed by the adjustment of all models weights.The application of the algorithm on integrated navigation system shows a high precision and switching speed,so it is applicable to dynamic systems.
%K Unscented Kalman filter
%K interacting multiple model
%K integrated navigation<br>Unscented卡尔曼滤波
%K 交互多模型
%K 组合导航
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=5104958AA00DEEB7FB3ECF765CD978F2&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=E158A972A605785F&sid=20ED669EB429E15C&eid=50B6AC44200581A5&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=7