The detection of a human being behind obstacles using radar technology has many promising applications, such as postdisaster search and rescue missions. In the case of large observation areas, the use of an unmanned aerial vehicle as the moving platform for radar is an appealing approach. However, this task is challenging because human vital signs provide a relatively weak signal compared with background noise and clutter. The drone's instability also negatively affects the obtained radar signal. Thus, this article presents a new signal processing method to extract and enhance respiration signals from drone-mounted radar. The method works by extracting the analytic signal representation and applying the subspace component segregation. Laboratory experiments in a controlled environment show that the proposed method can suppress a considerable level of vibration generated by unbalanced motor motion and enhance the respiration signal from radar data. A field experimental study using an octocopter in hovering mode confirms the method performs well in real-world conditions.

中文翻译：

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在悬停无人机上使用 UWB 脉冲雷达进行穿墙式人体呼吸检测

使用雷达技术检测障碍物背后的人有许多有前途的应用，例如灾后搜索和救援任务。在大观察区域的情况下，使用无人机作为雷达的移动平台是一种有吸引力的方法。然而，这项任务具有挑战性，因为与背景噪声和杂波相比，人类生命体征提供的信号相对较弱。无人机的不稳定性也会对获得的雷达信号产生负面影响。因此，本文提出了一种新的信号处理方法来提取和增强无人机车载雷达的呼吸信号。该方法通过提取解析信号表示并应用子空间分量分离来工作。在受控环境中的实验室实验表明，所提出的方法可以抑制由不平衡电机运动产生的相当大的振动水平，并增强来自雷达数据的呼吸信号。在悬停模式下使用八轴飞行器进行的现场实验研究证实，该方法在现实条件下表现良好。