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基于模糊数学与统计理论集成的多传感器数据融合方法
引用本文:项新建. 基于模糊数学与统计理论集成的多传感器数据融合方法[J]. 传感技术学报, 2004, 17(2): 197-199
作者姓名:项新建
作者单位:浙江科技学院,信息与电气工程系,杭州,310012
摘    要:利用格罗贝斯统计理论剔除系统误差数据.对余下的有效数据,利用模糊理论计算其与估计值之间的模糊贴近度,并以此确定每个传感器的重要性权重,最后提出数据融合公式实现多传感器的数据融合.应用实例验证了该方法的有效性.

关 键 词:模糊贴近度  格罗贝斯统计  传感器融合
文章编号:1004-1699(2004)02-0197-03
修稿时间:2003-09-16

A Method to Sensor Data Fusion Based on Fuzzy and Statistics Integration
XIANG Xinjian. A Method to Sensor Data Fusion Based on Fuzzy and Statistics Integration[J]. Journal of Transduction Technology, 2004, 17(2): 197-199
Authors:XIANG Xinjian
Abstract:A method to multi-sensor data fusion based on fuzzy and statistics integration is introduced. Measurement error data are deleted by Grubbs statistics theory. In aid to these remained data, the paper calculates the fuzzy similarity between the fuzzy numbers of measurements and predictions based on fuzzy theory, determinates the importance weigh of each sensor, proposes data fusion formula and realizes multi-sensor data fusion. Appilied example proves that the method is effective.
Keywords:fuzzy similarity  grubbs statistics  sensors data fusion
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