基于相关性函数和模糊贴近度的多传感器数据融合  

Multi-sensor Data Fusion Based on Correlation Function and Fuzzy Clingy Degree

作　　者：韩峰[1] 杨万海[1] 袁晓光[1] 

机构地区：[1]西安电子科技大学电子工程学院,西安710071

出　　处：《弹箭与制导学报》2009年第4期227-229,234,共4页Journal of Projectiles,Rockets,Missiles and Guidance

基　　金：陕西省教育厅基金(06JK281)资助

摘　　要：针对多传感器数据融合中,各传感器测量数据的可靠程度难以确定以及如何提高数据融合结果的精度问题。文中提出了利用模糊理论中的相关性函数来计算多传感器的相互支持程度,并基于模糊贴近度,对支持程度高的传感器数据进行融合。仿真结果表明,相比同类融合方法,该方法获得的结果具有更高的精度和可靠性。Focused on the problem that it is difficult to determine the reliability of each sensor and improve precision of the data fusion result in the process of the multi-sensors data fusion. In the paper, a new data fusion method based on correlation function and fuzzy clingy degree is proposed. The mutual supportability of multiple sensors is obtained from the correlation function. Then by the membership function, the reliability of information provide by each sensor is gained. Finally, the supposed fusion result can be produced on the basis of fuzzy clingy degree. The simulation experiment shows that the fusion results have higher precision and reliability compared with other methods.

关 键 词：多传感器 相关性函数 模糊贴近度 数据融合 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]