%0 Journal Article
%T Self-tuning information fusion Wiener predictor and its convergence<br>自校正信息融合Wiener预报器及其收敛性
%A DENG Zi-li
%A WANG Wei-ling
%A WANG Qiang
%A <br>邓自立
%A 王伟玲
%A 王强
%J 控制理论与应用
%D 2009
%I 
%X For the multisensor systems with correlated measurement noises and unknown noise statistics.the on-line noise statistics estimators are obtained by the correlation method. Under the linear minimum variance optimal information fusion criterion weighted by scalars for components,by the modem time series analysis method.a self-tuning decoupled fusion Wiener predictor is presented based on the identification of the moving average(MA) innovation models. By using the dynamic error system analysis(DESA) method,it is proved that the self-tuning fusion Wiener predictor converges to the optimal fusion Wiener predictor,so that it has the asymptotic optimality. Its accuracy is higher than that of each local self-tuning Wiener predictor. Its algorithm is simple.and is suitable for real time applications. A simulation example for a target tracking system shows its effectiveness.
%K multisensor information fusion
%K correlated measurement noises
%K noise statistics estimation
%K Lyapunov equation
%K self-tuning Wiener predictor
%K convergence
%K modern time series analysis method<br>多传感器信息融合
%K 相关观测噪声
%K 噪声统计估计
%K Lyapunov方程
%K 自校正wiener预报器
%K 收敛性
%K 现代时间序列分析方法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=F55094C2A1FA3E784CE750EF4DFD8506&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=708DD6B15D2464E8&sid=4AECDC3329847C4A&eid=F58A98E9A761BF85&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0