摘要
提出了一种基于支持度和自适应加权的阵列式传感器数据融合方法。其特点是通过关联融合多组测量信号序列以降低静态数据的随机测量误差。对单传感器测量信号序列,采用支持度方法计算每个测量数据的综合支持度和加权因子,然后对测量信号序列进行加权融合。对阵列式传感器多组测量信号序列,基于单传感器数据融合,利用自适应加权方法,在总均方误差最小意义下进行多组测量信号序列数据融合。仿真结果表明,该阵列式传感器数据融合方法是有效的。
An array-type sensor data fusion method is proposed to fuse multiple sequences of signal measurement and reduce the random measurement error of statistic data,based on support degree and adaptive weighted.For the sequence of signal measure-ment on the same sensor,the support degree is applied to calculate the comprehensive support degrees and weighting factors of all measurement to compute the weighted sum of the measurements.For the array-type sensors,the measurements on same sensor are processed firstly.Then,the adaptive weighting method is employed to fuse the data of various sensors to minimize the mean square error.The simulation result proves the effectiveness of proposed method.
出处
《中国科技论文》
CAS
北大核心
2014年第7期794-797,共4页
China Sciencepaper
基金
国家科技重大专项(2011ZX05020-006)
河北省自然科学基金资助项目(F2014203265)
高等学校博士学科点专项科研基金资助项目(20131333110015)
关键词
阵列式传感器
多组测量信号序列
数据融合
支持度
自适应加权
the array-type sensor
multiple measuring signal sequences
data fusion
support degree
adaptive weighted
