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多个相关测量的融合算法及其最优性
引用本文:欧连军,邱红专,张洪钺.多个相关测量的融合算法及其最优性[J].信息与控制,2005,34(6):690-695.
作者姓名:欧连军  邱红专  张洪钺
作者单位:北京航空航天大学自动化科学与电气工程学院,北京,100083
基金项目:国家自然科学基金重点资助项目(60234010)
摘    要:将不相关测量融合算法推广到了相关测量的融合.对两种方法进行了比较:第一种是先用本文提出的融合算法将多个相关测量进行融合,然后将融合后的测量用于Kalman滤波;第二种是直接将多个相关的测量用于Kalman滤波.理论分析证明两种方法是等价的,因而也证明了本文融合方法的最优性.仿真结果表明了理论分析的正确性.

关 键 词:多传感器测量融合  相关测量融合  数据融合  Kalman滤波
文章编号:1002-0411(2005)06-0690-06
收稿时间:2005-08-23
修稿时间:2005-08-23

Multiple Correlated Measurements Fusion Algorithm and Its Optimality
OU Lian-jun,QIU Hong-zhuan,ZHANG Hong-yue.Multiple Correlated Measurements Fusion Algorithm and Its Optimality[J].Information and Control,2005,34(6):690-695.
Authors:OU Lian-jun  QIU Hong-zhuan  ZHANG Hong-yue
Affiliation:School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
Abstract:The fusion algorithm of uncorrelated measurements is extended to the case of correlated measurements.Two methods are compared.One method uses the proposed algorithm to fuse multiple correlated measurements,then uses the fused measurement in the Kalman filtering.The other uses multiple correlated measurements directly in the Kalman filtering.Equivalence of the two methods are analyzed,and the optimality of the first method is then proved.Simulation result confirms the correctness of the theoretical analysis.
Keywords:multi-sensor measurement fusion  correlated measurement fusion  data fusion  Kalman filtering
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