Huang Yuhong, Zhao Youping
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China.
Sensors (Basel). 2025 Jul 22;25(15):4538. doi: 10.3390/s25154538.
Localization is one of the essential problems in the Internet of Things (IoT). Dynamic changes in the radio environment may lead to poor localization accuracy or discontinuous localization in non-line-of-sight (NLOS) scenarios. To address this problem, this paper proposes a localization enhancement method based on direct-path identification and tracking. More specifically, the proposed method significantly reduces the range error and localization error by quickly identifying the line-of-sight (LOS) to NLOS transition and effectively tracking the direct path. In a large testing hall, localization experiments based on the ultra-wideband (UWB) signal have been carried out. Experimental results show that the proposed method achieves a root mean square localization error of less than 0.3 m along the user equipment (UE) movement trajectory with serious NLOS propagation conditions. Compared with conventional methods, the proposed method significantly improves localization accuracy while ensuring continuous localization.
定位是物联网（IoT）中的关键问题之一。无线电环境中的动态变化可能会导致在非视距（NLOS）场景下定位精度低下或定位不连续。为了解决这个问题，本文提出了一种基于直线路径识别与跟踪的定位增强方法。具体而言，该方法通过快速识别视距（LOS）到NLOS的转变并有效跟踪直线路径，显著降低了距离误差和定位误差。在一个大型测试厅中，基于超宽带（UWB）信号进行了定位实验。实验结果表明，在存在严重NLOS传播条件的情况下，该方法沿用户设备（UE）移动轨迹实现的均方根定位误差小于0.3米。与传统方法相比，该方法在确保连续定位的同时显著提高了定位精度。
