标题： 基于深度相机生成的人体3D模型与电磁散射分析的非接触式雷达生理感知仿真 显示英文标题

标题： Simulation for Noncontact Radar-Based Physiological Sensing Using Depth-Camera-Derived Human 3D Model with Electromagnetic Scattering Analysis

摘要： 本研究提出了一种方法，用于模拟在呼吸监测期间由调频连续波雷达接收到的信号，该方法使用通过深度相机获取的人体几何形状和位移数据。 与以往依赖于简化人体几何模型或位移模型的研究不同，所提出的方法基于通过真实深度相机测量的人体形状和运动来建模高频散射中心。 在不同条件下对六名参与者进行了实验，包括不同的目标距离、坐姿方向和雷达类型，并同时从雷达和深度相机获取数据。 与传统基于模型的方法相比，所提出的技术在雷达图像、位移和频谱图的相关系数上分别提高了7.5%、58.2%和3.2%。 这项工作通过仿真促进了基于雷达的生理数据集的生成，并增强了我们对影响非接触传感精度因素的理解。 显示英文摘要

摘要： This study proposes a method for simulating signals received by frequency-modulated continuous-wave radar during respiratory monitoring, using human body geometry and displacement data acquired via a depth camera. Unlike previous studies that rely on simplified models of body geometry or displacement, the proposed approach models high-frequency scattering centers based on realistic depth-camera-measured body shapes and motions. Experiments were conducted with six participants under varying conditions, including varying target distances, seating orientations, and radar types, with simultaneous acquisition from the radar and depth camera. Relative to conventional model-based methods, the proposed technique achieved improvements of 7.5%, 58.2%, and 3.2% in the correlation coefficients of radar images, displacements, and spectrograms, respectively. This work contributes to the generation of radar-based physiological datasets through simulation and enhances our understanding of factors affecting the accuracy of non-contact sensing.