摘要
随着矿山物联网建设的推进,大量传感节点被放置在工作面、采空区等区域进行矿山安全监测。针对煤矿井下环境恶劣、定位不准确、定位精度不高等问题,提出一种基于高斯滤波的矿井接收信号强度(RSSI)定位算法(G-K-RSSI)。测距阶段,由于受到噪声干扰,对RSSI进行高斯滤波处理,通过周期测量路径损耗因子获得模型参数,对RSSI测距进行校正。定位阶段,利用未知节点与锚节点之间的误差,引入距离测量误差修正系数进行坐标定位。实验结果表明,G-K-RSSI算法的平均定位误差为2.1 m,定位精度远高于传统RSSI算法。
With the advancement of the construction of the Internet of Things in mines,a large number of sensor nodes are placed in areas such as working faces and goafs to monitor mine safety.Aiming at the problems of harsh underground environment,inaccurate positioning and low positioning accuracy in coal mines,an underground positioning algorithm(G-K-RSSI algorithm)is proposed,which uses Gaussian filtering to periodically measure the received signal strength(RSSI)of the path loss factor dynamically.In the ranging stage,due to noise interference,Gaussian filtering is performed on the RSSI,and the model parameters are obtained by periodically measuring the path loss factor to correct the RSSI ranging.In the positioning stage,the error between the unknown node and the anchor node is used to introduce the distance measurement error correction coefficient for coordinate positioning.The experimental results show that the average positioning error of the G-K-RSSI algorithm is 2.1 m,and its positioning accuracy is much higher than that of the traditional RSSI algorithm.
作者
乔欣
申海洋
况开通
李万豪
茆志魁
QIAO Xin;SHEN Haiyang;KUANG Kaitong;LI Wanhao;MAO Zhikui(School of Electronic Engineering,Chaohu University,Chaohu Anhui 238000,China)
出处
《重庆科技学院学报（自然科学版）》
CAS
2022年第2期84-88,共5页
Journal of Chongqing University of Science and Technology：Natural Sciences Edition
基金
安徽省高校自然科学基金重点项目“矿井无线电传输模型与动目标定位精度增强技术研究”(KJ2017A449)
巢湖学院质量工程项目“学分制下电类专业实验课程教学改革与实践”(CH20JXYJ25),“电路应用型课程开发与建设项目”(CH21YYKC02),“电路课程教学团队”(CH20JXTD03)。
