一种基于模糊理论的蒙特卡洛移动节点定位算法

A MCL MOBILE NODE LOCALISATION ALGORITHM BASED ON FUZZY THEORY

移动节点定位技术是无线传感器网络中的关键技术之一。针对蒙特卡洛算法MCL(Monte Carlo Localisation)在移动节点定位中存在样本需求量大、定位精度不高、定位所需时间长等缺点,提出基于模糊理论的改进蒙特卡洛移动节点定位算法F-MCL。通过对节点信号能量数值进行模糊化,滤波条件的精确化来弥补MCL的不足。仿真实验表明,提出的F-MCL算法比传统MCL算法在定位时间上比原来缩短了约58.6%,在定位精度上比MCL算法最高提高了约37%。

Mobile node localisation is one of crucial technologies in wireless sensor networks. Aiming at the defects of Monte Carlo local- isation （MCL） algorithm in mobile node localisation that the demand of samples amount is big, locating accuracy is low, and locating time is relatively long, we propose a new localisation algorithm F-MCL, which improves MCL mobile node localisation based on fuzzy theory. By the fuzzification of the node signal energy value and the precision of the filtering conditions we make up the deficiency of MCL. Simulation experi- ment shows that the proposed F-MCL algorithm shortens the time required for the localisation about 58.6% compared with the traditional MCL algorithm, and improves the precision of localisation about 37% than MCL.