应用雷达在复杂场景下检测生命体征时,为了解决现有的多人体目标检测和干扰滤除以及心跳信号干扰滤除的问题,提出了一种应用调频连续波(FMCW)雷达检测多目标生命体征信号的方法。首先,介绍了雷达检测原理与信号模型,阐述了整个雷达信号的处理流程,即多目标距离单元检测、相位提取、生命体征信号提取。其中在多目标距离检测过程中,提出1种改进的单元平均恒虚警率(CA-CFAR)算法,该方法具有自适应检测门限特点的同时,解决了传统CA-CFAR算法目标附近距离门重复检测的问题,实现多目标检测;在生命体征信号提取过程中,运用自动多尺度峰值检测(AMPD)算法估计呼吸率与心率,过滤无效的波峰干扰,提高对心跳检测的鲁棒性。最后,通过多组测试,相较于常用的频谱分析估算方法,呼吸速率和心率检测的平均误差率分别降低了3.67%和3.31%,验证了所提方法的可行性和准确性。
Abstract
The detection of non-contact human vital signs (such as respiration and heartbeat) based on radar, which has significant importance across various fields. One of these challenges, which the work seeks to solve, is the detection of multiple human targets and the filtering of interference, as well as the elimination of heartbeat signal interference in complex scenarios. To meet this need, a multi-target vital sign detection method, which relies on frequency modulated continuous wave (FMCW) radar, is proposed. After first introducing the radar detection principle and signal model, the entire radar signal processing flow is elucidated, which consists of multi-target distance unit detection, phase extraction, and vital sign signal extraction. In the process of multi-target distance detection, where challenges often arise, an improved Cell Averaging Constant False Alarm Rate (CA-CFAR) algorithm is proposed, a method that not only features adaptive detection thresholds but also solves the problem of repeated distance gate detection near targets in traditional CA-CFAR algorithms, thus achieving multi-target detection. During the vital sign signal extraction process, the Automatic Multi-Scale Peak Detection (AMPD) algorithm is utilized so that breathing and heart rates can be estimated, filtering out invalid peak interferences, which enhances the robustness of heartbeat and respiration rate detection. Finally, through multiple sets of tests, which are conducted to verify the methodology, the average error rates for breathing rate and heart rate detection are found to have reduced by 3.67% and 3.31%, respectively, when compared to commonly used spectral analysis estimation methods, the feasibility and accuracy of the proposed method are validated.
关键词
生命体征检测 /
非接触测量 /
调频连续波雷达 /
自动多尺度峰值检测 /
心率 /
呼吸速率
Key words
vital sign detection;non-contact measurement;FMCW;AMPD /
heart rate /
breathing rate
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基金
中国计量大学毫米波雷达联合实验室基金项目(2022-2024-03103-21179)
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