Abstract：Ultra-wideband (UWB) life detection radar has found wide applications in anti-riot, rescue, and anti-terrorism actions due to its many advantages, such as strong penetrating ability, high distance resolution, and strong anti-interference ability. Therefore, research on human micro-tremor signal detection using UWB through-wall radar has much significance. As the echo signal of through-wall life detection radar is interfered by background noise clutter, the conventional method using the digital filter cannot effectively detect human micro-tremor signal. To solve this problem, this paper presents a human body micro-tremor signal detection algorithm. First, the frequency domain cumulation is used to increase the signal-to-noise ratio (SNR) of the echo signal, and then EMD is used for de-noising. This algorithm not only has the advantages of frequency domain cumulation, but also has the ability of EMD method for adaptive decomposition. Under low SNR, it overcomes the disadvantages of frequency domain cumulation and EMD method, the former being not real-time and the latter having ineffective clutter remove. The simulation results show that the algorithm not only improves the SNR of the radar echo signal, but also overcomes the disadvantage of frequency domain cumulation. The frequency of human respiration can be rapidly and accurately detected by processing the echo signal using this algorithm, which is a novel method for through-wall radar detection of weak signals.
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