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

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.