%0 Journal Article
%T Uncertainty Analysis Based Dynamic Multi-Sensor Data Fusion<br>一种基于不确定分析的多传感器信息动态融合方法
%A LUO Ben-Cheng
%A YUAN Kui
%A CHEN Jin-Long
%A ZHU Hai-Bing
%A <br>罗本成
%A 原魁
%A 陈晋龙
%A 朱海兵
%J 自动化学报
%D 2004
%I 
%X The problem of modeling multi-sensor data fusion system under uncertainty is discussed. Taking advantage of the measure of relative proximity in terms of uncertainty, the authors firstly implement multi-sensor dynamic clustering. Based on Bayesian estimation technology and the measure of compatibility, an optimal fusion paradigm for multi-sensors data fusion in the same group is presented. By examining the mutual im-pact of sensor groups based on the measure of confidence, a novel model for dynamic multi-sensor fusion system is described. The efficient fusion of data from different sources enables the system to respond promptly to the uncertain environment. Finally, experiments demonstrate the model is of higher sensitivity and practicability,especially in uncertain environment for intelligent systems.
%K Uncertainty analysis
%K measure of relative proximity
%K dynamic multi-sensor data fusion
%K optimal Bayesian estimation fusion<br>不确定分析
%K 格贴近度
%K 动态多传感器信息融合
%K 最优Bayesian估计融合
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=D0FCCE6BE9F6B59F&yid=D0E58B75BFD8E51C&vid=340AC2BF8E7AB4FD&iid=38B194292C032A66&sid=8CCD0401CC9AE432&eid=BFB86B6ED3A99B9D&journal_id=0254-4156&journal_name=自动化学报&referenced_num=5&reference_num=16