隧道内超宽带车载标签跟踪方法  

UWB vehicle tag tracking method in tunnels

作　　者：吴尧帅 费天乐 WU Yaoshuai;FEI Tianle(Henan Shunbo Building Intelligent Technology Co.,Ltd.,Zhengzhou 450000,China;School of Engineering,University of Central Lancashire,Preston,Lancashire PR12HE,UK)

机构地区：[1]河南顺博智能科技有限公司,郑州450000 [2]中央兰开夏大学工程学院,兰开夏郡普雷斯顿PR12HE

出　　处：《导航定位学报》2024年第4期181-189,共9页Journal of Navigation and Positioning

摘　　要：针对隧道中车辆跟踪难、精度不高的问题,设计了一个基于超宽带技术(UWB)的车载标签跟踪方法。在跟踪算法上,首先利用基于UWB的到达时间差(TDOA)算法对车载标签进行实时定位;再通过一种适用于隧道特征的自适应卡尔曼滤波方法,有效估计了隧道内车载标签位置。在硬件设计上,将STM32系列芯片作为中央处理器(CPU),DW1000作为核心通信元器件制作了基站与车载标签。在京广路隧道进行实验测试与分析,结果表明该方法在隧道内能够对车辆进行跟踪,且整体误差小于30 cm,实现了车辆在隧道内的实时跟踪。Aiming at the problem of difficulty and low accuracy in tracking vehicles in tunnels,a vehicle tag tracking method based on ultra-wide band(UWB)technology was designed.In terms of tracking algorithm,firstly,the UWB-based time difference of arrival(TDOA)algorithm was used to locate the vehicle tag in real time;then an adaptive Kalman filtering method suitable for tunnel characteristics was used to effectively estimate the position of the vehicle tag in the tunnel.In terms of hardware design,the STM32 series chip was used as the central processing unit(CPU)and the DW1000 was used as the core communication component to make the base station and vehicle tags.Experimental testing and analysis were carried out in the Jingguang Road Tunnel,the results showed that the method can track vehicles in the tunnel,and the overall error is less than 30 cm,achieving real-time tracking of vehicles in the tunnel.

关 键 词：超宽带技术 到达时间差 自适应卡尔曼滤波 车载标签 

分 类 号：P228[天文地球—大地测量学与测量工程]