国家自然科学基金(62172394); 中国科学院青年创新促进会(2020109); 中日韩A3前瞻计划(62061146001); 北京大学基金会北京大学-南洋理工大学合作基金
近年来, 对运动目标的定位和追踪被广泛地应用于室内导航、智能家居、安防监控和智慧医疗等场景. 基于无线射频信号的非接触式定位追踪受到了研究人员的广泛关注, 其中基于商用IR-UWB的技术能够以较低的成本和功耗实现目标定位和追踪的功能, 具有较强的发展潜力. 然而, 现有工作大多存在以下问题: 1)追踪场景受限, 只针对理想情况下室外或者相对空旷的室内场景进行建模和处理; 2)目标的运动状态受限且建模过于理想; 3)虚假动态目标引起的追踪精度不足. 为了解决这些问题, 在理解多径场景下接收信号谱组成的基础上, 提出一个基于IR-UWB的动态目标追踪方法. 首先提取原始信号谱中动态成分, 并利用基于高斯模糊的多径消除和距离提取算法, 消除了多径干扰, 仅保留与运动目标直接相关的一次反射信息, 从而准确地获取了目标的距离变化曲线. 随后, 提出多视角融合算法, 将不同视角上的设备距离信息进行融合, 实现对自由活动目标的准确定位和追踪. 此外, 还搭建一个基于低成本商用IR-UWB雷达的实时动态目标追踪系统. 真实室内家居场景中的实验结果表明, 系统估计的人体中心的位置与真实运动轨迹的误差始终小于20 cm. 在改变实验环境、实验者、活动速度、设备高度等影响因素的情况下, 系统依然鲁棒.
In recent years, the localization and tracking of moving targets have been widely used in scenes including indoor navigation, smart homes, security monitoring, and smart medical services. Radio frequency (RF)-based contactless localization and tracking have attracted extensive attention from researchers. Among them, the commercial IR-UWB-based technology can achieve target localization and tracking at low costs and power consumption and has strong development potential. However, most of the existing studies have the following problems: 1) Limited tracking scenes. Modeling and processing methods are only for outdoor or relatively empty indoor scenes under ideal conditions. 2) Limited movement states of targets and unduly ideal modeling. 3) Low tracking accuracy caused by fake moving targets. To solve these problems, this study proposes a moving target tracking method using IR-UWB on the basis of understanding the composition of the received signal spectrum in multipath scenes. First, the dynamic components of the originally received signal spectrum are extracted. Then, the Gaussian blur-based multipath elimination and distance extraction algorithm is employed to eliminate multipath interference, which only retains primary reflection information directly related to the moving target and therefore accurately obtains the distance variation curve of the target. Subsequently, a multi-view fusion algorithm is proposed to fuse the distance information of the devices from different views to achieve accurate localization and tracking of a single freely moving target. In addition, a real-time moving target tracking system based on the low-cost commercial IR-UWB radar is established. The experimental results in the real indoor home scene show that the error between the center position of the human body estimated by the system and the real motion trajectory is always within 20 cm. Moreover, the system remains robust even if influencing factors such as the experimental environment, experimenter, activity speed, and equipment height are altered.