Study on Respiration Signal Detection Algorithm of Ultra-WideBand Through-wall Radar Based on A
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摘要: 废墟下呼吸信号的检测对地震救援具有重要意义。在实际中，障碍物(如墙体)后的人体呼吸信号会被环境中的噪声所掩盖。如何提升穿墙呼吸信号的信噪比(SNR)仍是一项具有挑战性的工作。该文提出一种基于先验信噪比估计的检测算法，用于增强穿墙弱呼吸信号的输出SNR。该算法在谱减法中典型的决策导向(DD)算法基础上加入了自适应权重因子，通过降低先验信噪比的估计误差来进一步消除残余随机噪声。通过仿真和实验验证了所提出算法的性能。与传统的快速傅里叶变换(FFT)、奇异值分解(SVD)和DD检测算法相比，所提出的呼吸检测算法的输出SNR有所提高。Abstract: The detection of respiration signal under the ruins is of great significance to earthquake rescue. In reality, the human respiration signal behind the obstacle (such as walls) will be masked by noise in the environment. How to improve the Signal-to-Noise Ratio (SNR) of the through-wall respiration signal is still a challenging task. A detection algorithm based on a priori SNR estimation for enhancing the output SNR of the weak through-wall respiration signal is proposed in this paper. Based on the typical Decision-Directed (DD) algorithm of spectral subtraction methods, an adaptive weighting factor is added in the proposed algorithm to eliminate further the residual random noise by reducing the estimation error of the a priori SNR. The performance of the proposed algorithm is investigated through simulation and experimental verification. The output SNR of the proposed respiration detection algorithm is improved compared with the traditional Fast Fourier Transform (FFT), Singular Value Decomposition (SVD), and DD detection algorithm.
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表 1 不同墙体厚度下的输出SNR (dB)
墙厚(m) 0.12 0.24 0.37 FFT算法 12.13 11.10 10.06 SVD算法 18.97 17.28 14.37 DD算法 26.34 23.30 18.41 所提算法 32.83 30.80 27.67 
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