基于Kalman滤波的多传感器分布式数据融合算法及其并
行实现
作者：郭强;郁松年
作者机构：School of Computer Engineering and Science, Shanghai University, Shanghai 200072, P.R. China;School of Computer
Engineering and Science, Shanghai University, Shanghai 200072, P.R. China
来源：上海大学学报（英文版） ISSN：1007-6417 年：2006 卷：010 期：002 页码：118-122 页数：5 中图分类：TP3 正文语种：chi
关键词：data fusion;Kalman filtering;multisensor systems;distributed estimation
摘要：The purpose of data fusion is to produce an improved model or estimate of a system from a set of independent data sources. Various multisensor data fusion approaches exist, in which Kalman filtering is important. In this paper, a fusion algorithm based on multisensor systems is discussed and a distributed multisensor data fusion
algorithm based on Kalman filtering presented. The algorithm has been implemented on cluster-based high performance computers.
Experimental results show that the method produces precise estimation in considerably reduced execution time.
基于Kalman滤波的多传感器分布式数据融合算法及其并行实现
