一种基于联邦Kalman滤波结构的自适应信息融合方法  

An Adaptive Multi-sensor Information Fusion Algorithm Based on Federated Kalman Filter

作　　者：苏丽媛[1] 范新南[1] 郭建甲[1] 金纪东[1] 

机构地区：[1]河海大学计算机及信息工程学院,江苏常州213022

出　　处：《河海大学常州分校学报》2005年第4期5-7,11,共4页Journal of Hohai University Changzhou

摘　　要：鉴于联邦Kalman滤波是一种能在复杂信息融合系统中进行目标状态估计的有效方法,介绍了联邦Kalman滤波器的原理和结构,提出了一种基于联邦Kalman滤波结构的自适应多传感器信息融合算法.仿真结果表明,该算法能有效提高信息融合系统的精度和容错性,具有较高的实用价值.The federated Kalman filter is an effective strategy used in target estimate in a complex MSIF （Multi-Sensor Information Fusion） system. The elements and the frame of federated Kalman filter are introduced in this paper. And an adaptive MSIF algorithm based on federated Kalman filer is presented. The simulation results show that the algorithm can improve system accuracy and faulttolerant property, and therfore has high value in practice.

关 键 词：联邦Kalman滤波 多传感器信息融合 自适应 

分 类 号：TM212.6[一般工业技术—材料科学与工程]