基于数据插值和权重指数的矿井机车无线定位方法  

A wireless positioning method based on data interpolation and weighted index for mine locomotive

作　　者：杨成[1] 冯琳[1] 魏振春[1] 卫星[1] 

机构地区：[1]合肥工业大学计算机与信息学院,安徽合肥230009

出　　处：《合肥工业大学学报（自然科学版）》2013年第11期1331-1334,共4页Journal of Hefei University of Technology：Natural Science

基　　金：国家物联网发展专项资金计划资助项目(工信部科〔2012〕583号);安徽省国际科技合作计划基金资助项目(10080703001);江苏省自然科学基金资助项目(BK2011236);安徽省自然科学基金资助项目(1208085QF113)

摘　　要：文章将基于WLAN的无线定位方法应用于矿井下,针对指纹识别定位算法在训练阶段开销过大的问题,结合矿井巷道一维线状特性,提出了一种基于区域划分的神经网络插值算法和基于信号强度权重指数的定位算法,在提高算法效率的同时,减小了平均定位误差。仿真结果表明,相比于传统的指纹识别定位算法,该算法在效率分别提高33%、20%和10%的情况下,定位精度分别提高了9%、15%和23%。Wireless local area network（WLAN）-based wireless positioning technology is applied to the mine, a neural network interpolation algorithm based on region division and a wireless positioning method based on signal strength weighted index are proposed to solve time-consuming problem in training phase of fingerprint identification positioning algorithm, and the one-dimensional linear fea- ture of mine laneway is considered. The proposed positioning method improves the efficiency and re-duces the average positioning error. The experimental result shows that compared with traditional fin-gerprint positioning method, the proposed positioning method improves the average positioning accu-racy by 9%, 15% and 23% in such cases that the efficiency increases by 33%, 20% and 10% respec- tively.

关 键 词：无线局域网 无线定位 信号强度 神经网络插值 权重指数 

分 类 号：TN98[电子电信—信息与通信工程]