摘要
针对WSN监测系统的目标检测与分类问题,提出一种基于直觉模糊推理(IFR)的多源数据融合方法。由模糊推理的思想,设计各状态变量的属性函数。根据目标声强变化和引起的地磁场变化的模型,设计模糊推理规则,并检验了所建规则的合理性。理论分析与仿真结果的对比表明算法能准确地对目标进行分类,且运算量小,适用于计算能力较弱的WSN节点。
Aimed at the issue about the targets detection and classification in target monitoring system based on WSN, the study proposed a multi-sensor data fusion method based on intuitionistic fuzzy reasoning （ IFR ）. The property functions of two status variables were designed according to the method of fuzzy reasoning. The study constructed the inference rules of the system after acoustic energy attenuation model and the variety of magnetic field model were built, and the rationality of constructed rules was checked. The comparison between theoretical analysis and simulation result show that intuitionistic fuzzy reasoning can classify targets uncomplicatedly and effectively. Because of its less calculation, the method can apply to WSN node, in which the calculation capacity is weak.
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2013年第5期180-184,共5页
Journal of National University of Defense Technology
关键词
无线传感器网络
数据融合
目标分类
直觉模糊推理
wireless sensor network （WSN）
data fusion
target classification
intuitionistic fuzzy reasoning（IFR）
作者简介
潘仲明（1959-），男，教授，博士，博士生导师，Email：chungmingpan@163.com
