%0 Journal Article
%T Correlated Measurement Fusion Steady-state Kalman Filtering Algorithms and Their Optimality<br>相关观测融合稳态Kalman滤波器及其最优性
%A RAN Chen-Jian
%A HUI Yu-Song
%A GU Lei
%A DENG Zi-Li
%A <br>冉陈键
%A 惠玉松
%A 顾磊
%A 邓自立
%J 自动化学报
%D 2008
%I 
%X For the multisensor systems with correlated measurement noises and different measurement matrices,two correlated measurement fusion steady-state Kalman filtering algorithms are presented by using the weighted least squares (WLS)method.The principle is that a fused measurement equation is obtained by weighting the local measurement equations,and then it accompanies the state equation to realize the measurement fusion steady-state Kalman filtering. By using the information filter,it is proved that they are functionally equivalent to the centralized fusion steady-state Kalman filtering algorithm,so that they have the asymptotic global optimality,and they can reduce the computational burden.They can be applied to the measurement fusion filtering and deconvolution for multichannel autoregressive moving average(ARMA)signals.Two numerical simulation examples verify their functional equivalence.
%K Multisensor information fusion
%K measurement fusion
%K correlated measurement noises
%K steady-state Kalman filtering
%K optimality<br>传感器信息融合
%K 观测融合
%K 相关观测噪声
%K 稳态Kalman滤波
%K 最优性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=F2BA2F7D825261E195627FB0F73EB6D3&yid=67289AFF6305E306&vid=339D79302DF62549&iid=38B194292C032A66&sid=FD7C952458BFB5D8&eid=1DF3F9D75A12D97B&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=10