基于WSN的目标探测与分类算法

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。

Targets detection and classification based on WSN

Aiming 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 are designed according to the method of fuzzy reasoning. The study construct the inference rules of the system after acoustic energy attenuation model and the variety of magnetic field model are built, and the rationality of constructed rules is 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 on WSN node, which calculation capacity is weak.