基于自组织竞争网络的井下人员定位融合算法  

Fusion algorithm of underground personnel positioning based on self-organizing competitive network

作　　者：张剑英[1] 张跃辉[1] 周立宇[1] 

机构地区：[1]中国矿业大学信息与电气工程学院,江苏徐州221116

出　　处：《工矿自动化》2016年第3期44-47,共4页Journal Of Mine Automation

摘　　要：针对基于加权质心算法的井下人员定位方法误差大的问题,提出了一种基于自组织竞争网络的井下人员定位融合算法。该算法利用自组织竞争网络的学习筛选能力,通过分组训练筛选出接近理论值的实际RSSI值,找出用于加权质心算法的有效坐标,在加权质心算法的基础上计算未知节点位置。Matlab仿真结果表明,该算法的定位精度比原加权质心算法显著提高。In view of problem of big positioning error of underground personnel positioning method based on weighted centroid algorithm, a fusion algorithm of underground personnel positioning based on self-organizing competitive network was proposed. The algorithm uses learning screening capacity of self- organizing competitive network, and screens out actual RSS! value close to the theoretical value by group training, then finds valid coordinates for the weighted centroid algorithm, and calculates unknown node position based on weighted eentroid algorithm. The Matlab simulation results show that the positioning accuracy of the algorithm is significantly higher than the original weighted eentroid algorithm.

关 键 词：无线传感网络 人员定位 自组织竞争网络 加权质心 

分 类 号：TD655.3[矿业工程—矿山机电]