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推进用于搜索和救援的远程生命传感：一种通过机载超宽带雷达精确检测生命体征的新型框架。

Advancing Remote Life Sensing for Search and Rescue: A Novel Framework for Precise Vital Signs Detection via Airborne UWB Radar.

作者信息

Jing Yu, Yan Yili, Li Zhao, Qi Fugui, Lei Tao, Wang Jianqi, Lu Guohua

机构信息

Department of Military Biomedical Engineering, Air Force Medical University, Xi'an 710032, China.

出版信息

Sensors (Basel). 2025 Aug 22;25(17):5232. doi: 10.3390/s25175232.

DOI:10.3390/s25175232
PMID:40942663
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12431357/
Abstract

Non-contact vital signs detection of the survivors based on bio-radar to identify their life states is significant for field search and rescue. However, when transportation is interrupted, rescue workers and equipment are unable to arrive at the disaster area promptly. In this paper, we report a hovering airborne radar for non-contact vital signs detection to overcome this challenge. The airborne radar system supports a wireless data link, enabling remote control and communication over distances of up to 3 km. In addition, a novel framework based on blind source separation is proposed for vital signals extraction. First, range migration caused by the platform motion is compensated for by the envelope alignment. Then, the respiratory waveform of the human target is extracted by the joint approximative diagonalization of eigenmatrices algorithm. Finally, the heartbeat signal is recovered by respiratory harmonic suppression through a feedback notch filter. The field experiment results demonstrate that the proposed method is capable of precisely extracting vital signals with outstanding robustness and adaptation in more cluttered environments. The work provides a technical basis for remote high-resolution vital signs detection to meet the increasing demands of actual rescue applications.

摘要

基于生物雷达对幸存者进行非接触式生命体征检测以识别其生命状态，对于野外搜救具有重要意义。然而，当交通中断时，救援人员和设备无法及时抵达灾区。在本文中，我们报告了一种用于非接触式生命体征检测的悬停机载雷达，以克服这一挑战。该机载雷达系统支持无线数据链路，能够在长达3公里的距离上进行远程控制和通信。此外，还提出了一种基于盲源分离的新颖框架用于生命信号提取。首先，通过包络对齐补偿平台运动引起的距离徙动。然后，通过特征矩阵联合近似对角化算法提取人体目标的呼吸波形。最后，通过反馈陷波滤波器抑制呼吸谐波来恢复心跳信号。现场实验结果表明，所提方法能够在更复杂的环境中精确提取生命信号，具有出色的鲁棒性和适应性。这项工作为远程高分辨率生命体征检测提供了技术基础，以满足实际救援应用不断增长的需求。

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