基于RSSI的煤矿巷道高精度定位算法研究  

Precision positioning algorithm in coal mine tunnel based on RSSI

作　　者：李论[1] 张著洪[1] 丁恩杰[2] 张雷[2] 

机构地区：[1]贵州大学大数据与信息工程学院,贵州贵阳550025 [2]中国矿业大学物联网(感知矿山)研究中心,江苏徐州221008

出　　处：《中国矿业大学学报》2017年第1期183-191,200,共10页Journal of China University of Mining & Technology

基　　金：国家重点基础研究发展计划(973)项目(2014CB046305);国家自然科学基金项目(61563009)

摘　　要：无线精确定位被广泛应用于矿山物联网技术领域,针对煤矿巷道定位算法普遍存在定位精度不高、误差大、易受环境干扰、被定位目标抖动和漂移等问题,提出一种基于高斯滤波的分段实时计算动态路径损耗因子α和环境参量ε_σ的接收信号强度指标(RSSI)高精度巷道定位算法.实验中采用加权最小二乘法和最小二乘法曲线拟合方法,实时动态计算路径损耗因子和环境参量来构建符合煤矿井下特殊环境的信号传输模型;在位置坐标求解阶段引入距离误差修正参数Δμ,采用标准最小均方差迭代估计出未知节点的位置坐标.以锚节点不同布置方案对算法进行实地测距验证.结果表明:提出的算法定位平均精度为1.6m,最坏情况是2.8m,横向平均误差为1.2m,纵向平均误差为0.8m;相比固定路径损耗因子的RSSI算法提高了定位精度,降低了误差率.Wireless precise positioning has been widely used in mine internet of things. In viewof the problems extant in mine tunnel positioning algorithm like low positioning accuracy, high error rate, susceptibility to environmental interference, jitter and drifting of target located, a high precision Received Signal Strength Indicator （RSSI） positioning algorithm based on Gaussian-a-RSSI algorithm for coal mine was proposed. The path loss factor α and the environ- ment parameter factor εσ were calculated by piecewise fitting method based on Gaussian filter. Weighted least square method and least squares curve fitting were adopted to simulate the sig- nal transmission of actual mine tunnel environment through a large body of measured data. The signal transmission model of the actual environment was built and the distance between the an- chor nodes and unknown nodes was calculated. The distance error parameter Δμ was intro- duced in the positional elaboration phase and locating node coordinates were estimated by the standard minimum mean square error iteration. Finally, precision positioning verification of the Gaussian-a-RSSI algorithm was conducted with different typical layouts of anchor nodes. The measurement error and the positioning error of the algorithm were theoretically analyzed in de-tail.According to the test results, the average positioning accuracy is about 1.6 m, the largesterror is 2.8 m, the lateral and vertical average error is 1.2 m and 0. 8 m respectively. Com-pared with the RSSI algorithm based on fixed path loss factor, the positioning algorithm pro-posed in this paper can improve positioning accuracy and reduce error rate.

关 键 词：煤矿巷道 无线定位 RSSI 高精度 定位算法 

分 类 号：TP929.4[自动化与计算机技术]