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摘要
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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