摘要
主要研究粮情测控系统的特征级信息融合,采用基于Bayes理论的数据融合方法把多个异质传感器提供的数据进行特征级融合处理,以提高系统低层数据融合的准确度和稳定性;提出基于Bayes理论的粮情特征级融合的模型和算法.通过实验,验证了此模型的有效性,有效解决了粮情测控系统低层次特征级融合的不确定性和不精确性的问题.
The Feature-level information fusion of grain measurement and control system was investigated. A Bayes theory-based data fusion method was used to carry out feature-level fusion of data provided by multiple heterogeneous sensors to improve the fusion accuracy and the stability of low-level data. A Bayes theory-based grain feature - level fusion model and algorithm were pointed out. The validity of the model is verified by experiment to effectively solve the problem of the uncertainty and inaccuracy of the low feature-level information fusion of the grain measurement and control system.
出处
《河南工业大学学报（自然科学版）》
CAS
北大核心
2009年第4期77-80,共4页
Journal of Henan University of Technology：Natural Science Edition
基金
"十一五"国家科技支撑计划重点项目(2008BADA8B03)
关键词
粮情测控
多传感器
信息融合
Bayes理论
grain measuremen and control
multi-sensor
information fusion
Bayes theory
