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使用波束控制雷达架构对人体进行精确定位和生命体征检测的增强技术。

Enhanced Technique for Accurate Localization and Life-Sign Detection of Human Subjects Using Beam-Steering Radar Architectures.

作者信息

Mercuri Marco, Sacco Giulia, Hornung Rainer, Visser Huib, Lorato Ilde, Pisa Stefano, Veltri Pierangelo, Dolmans Guido

出版信息

IEEE Trans Biomed Eng. 2025 Feb;72(2):552-564. doi: 10.1109/TBME.2024.3463199. Epub 2025 Jan 21.

Abstract

In this work, we propose a signal processing technique for beam-steering radar architectures allowing concurrent two-dimensional (2-D) localization and vital signs monitoring of human subjects. We demonstrated it by using a single-input single-output (SISO) frequency-modulated continuous wave (FMCW) radar which integrates two frequency-scanning antennas (FSAs). This method is capable of isolating the Doppler signal generated by each single subject from the contributions of all the reflections in the monitored environment. This allows determining the number of individuals in the room and accurately measuring their vital signs parameters (respiration and heart rates) and 2-D positions (range and azimuth information). The spectral analysis, the data matrix generation and the signal processing technique are detailed and discussed. Experimental results demonstrated the feasibility of the proposed approach, showing the ability in determining the number of subjects present in the room, in accurately measuring and tracking over time their vital signs parameters, and in 2-D localization with errors within the limits of the radar range and angular resolutions. Practical applications arise for healthcare, Hospital 4.0, Internet of Medical Things (IoMT), ambient assisted living, smart buildings and through-wall sensing.

摘要

在这项工作中,我们提出了一种用于波束控制雷达架构的信号处理技术,该技术允许对人体进行并发二维(2-D)定位和生命体征监测。我们通过使用集成了两个频率扫描天线(FSA)的单输入单输出(SISO)调频连续波(FMCW)雷达对其进行了演示。该方法能够将每个个体产生的多普勒信号与监测环境中所有反射的贡献隔离开来。这使得能够确定房间内的个体数量,并准确测量他们的生命体征参数(呼吸和心率)以及二维位置(距离和方位信息)。详细介绍并讨论了频谱分析、数据矩阵生成和信号处理技术。实验结果证明了所提方法的可行性,展示了其确定房间内受试者数量、随时间准确测量和跟踪他们的生命体征参数以及在二维定位中误差在雷达距离和角度分辨率范围内的能力。该技术在医疗保健、医院4.0、医疗物联网(IoMT)、环境辅助生活、智能建筑和穿墙传感等领域具有实际应用价值。

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