基于相关性函数的多传感器自适应加权融合算法  

Multi-Sensor Adaptive Weighted Fusion Algorithm Based on Correlation Function

作　　者：丁辉[1] 仲跃 张俊 钱建中 

机构地区：[1]安徽工业大学机械学院,安徽马鞍山243032 [2]盐城市水利局,江苏盐城224005 [3]盐城市盐都区水务局,江苏盐城224005

出　　处：《重庆理工大学学报（自然科学）》2016年第2期114-118,共5页Journal of Chongqing University of Technology：Natural Science

基　　金：江苏省水利科技项目(2014078)

摘　　要：针对多传感器实际测量中个别传感器出现的数据偏离现象,提出基于相关性函数的自适应加权融合算法。利用相关性函数对数据进行预处理,计算各传感器间的相互支持程度,对于偏离较为明显的数据,用相关性大的数据进行替换;再通过多传感器自适应加权融合算法对数据进行融合。利用该算法对相关数据进行处理,经计算分析得到融合结果为0.999 7,并与传统自适应加权融合算法以及极大似然法的计算结果进行对比。分析结果表明:算法的融合结果更接近实际,融合精度较高。Aiming at the phenomenon that a sensor may get biased data in the process of multi-sensor measurement,the multi-sensor adaptive weighted fusion algorithm based on correlation function was put forward. The data was preprocessed by correlation function,and then the mutual supportability of each sensor was calculated. In terms of the obvious biased data,they were replaced by high correlation data. Finally,the data was fused by using multi-sensor adaptive weighted fusion algorithm. Therelated data was processed by using the algorithm. The fusion result,which is 0. 999 7,was obtained via calculation and analysis. Moreover,it was compared with traditional adaptive weighted fusion algorithm and maximum likelihood method. The result shows that the fusion result based on the algorithm is close to the real situation and has a higher precision.

关 键 词：多传感器 自适应加权融合 相关性函数 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]