基于Wi-Fi指纹的煤矿井巷目标追踪实验设计

Experimental design of coal mine tunnel target tracking based on Wi-Fi fingerprints

基于“应急通信技术”课程实践教学环节,为了让学生用较少时间获得更好的目标追踪效果,创新设计了基于Wi-Fi指纹的煤矿井巷目标追踪实验。首先提出一种基于信号接入点测量准确度(accuracy base on access point measurement,ABAPM)的在线动态匹配算法,以解决信号接入点(access point,AP)与待定位目标之间被移动物体遮挡情况下信号传输受限问题;然后利用K-Means++算法降低在线匹配阶段运行时间;最后联合ABAPM算法与卡尔曼滤波实现煤矿井巷携带标签目标的轨迹追踪。仿真与实测结果表明:在煤矿井巷环境中,基于ABAPM算法的Wi-Fi指纹目标追踪能够有效判断AP准确度,保障偶然被遮挡目标的定位精度和追踪效果,且耗时较短。

Based on the practical teaching link of the“Emergency communication technology”course,and in order to enable students to obtain better target tracking effect in less time,a coal mine tunnel target tracking experiment based on Wi-Fi fingerprints is innovatively designed.Firstly,an online dynamic matching algorithm ABAPM(accuracy based on access point measurement)is proposed to solve the problem of limited signal transmission when the access point(AP)and the target to be located in the coal mine tunnel are blocked by moving objects.Then K-means++algorithm is used to reduce the running time of online matching stage.Finally,the ABAPM algorithm is combined with Kalman filter to realize the trajectory tracking of coal mine tunnel tag targets.The simulation and measured results show that the Wi-Fi fingerprint target tracking based on the ABAPM algorithm can effectively judge the accuracy of AP,guarantee the positioning accuracy and tracking effect of occasionally blocked targets,and it takes a short time in the coal mine tunnel environment.