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Vital Signs Detection Based on UWB Radar Using Trajectory Capture and Peak Capture

机译:基于UWB雷达轨迹捕获和峰值捕获的生命体征检测

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A novel vital sign detection algorithm based on trajectory capture and peak capture is proposed to solve the problem that the heartbeat signal of slightly moving subjects is easily interfered by breathing harmonics and other clutter. First, the received signal is processed by the average cancellation method to suppress the stationary clutter. Then, we use the trajectory capture algorithm to catch the moving trajectory of the subject, use the trajectory to correct each received pulse, and use the distance gate selection algorithm to extract the body surface vibration signal. After that, the body surface vibration signal was subjected to low-pass filtering in the frequency domain and autocorrelation processing to improve the signal-to-noise ratio of the signal. Finally, the frequency-domain peak capture algorithm of N iterations was used to extract the vital signs of the signal. Simulation results show that the algorithm can accurately extract the vital signs of slightly moving subjects, and has higher measurement accuracy and better stability than the traditional algorithm.
机译:提出了一种基于轨迹捕获和峰值捕获的新型生命体征检测算法,以解决轻度运动对象的心跳信号容易受到呼吸谐波和其他杂波干扰的问题。首先,通过平均消除方法对接收到的信号进行处理,以抑制静止杂波。然后,我们使用轨迹捕获算法来捕获对象的运动轨迹,使用轨迹来校正每个接收到的脉冲,并使用距离门选择算法来提取身体表面振动信号。之后,对身体表面振动信号进行频域低通滤波和自相关处理,以提高信号的信噪比。最后,使用N次迭代的频域峰值捕获算法提取信号的生命体征。仿真结果表明,与传统算法相比,该算法能够准确地提取微动对象的生命体征,具有更高的测量精度和更好的稳定性。

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