Ground penetrating radar weak signals denoising via semi-soft threshold empirical wavelet transform

Abstract

Ground penetrating radar (GPR) weak signals have the characteristics of low signal-To-noise ratio (SNR) and high frequency, which is a major challenge to noise attenuation. In this paper, we propose a GPR denoising approach based on empirical wavelet transform (EWT) combined with semi-soft thresholding. According to the frequency characteristics of signal, a spectrum segmentation strategy is designed. It can adaptively decompose signal and noise into different modes. The mode which contains more valid signals is processed by hard thresholding to reserve amplitude; the other modes which contain useless signals are processed by soft threshold functions to maintain the continuity of the signal. After weak signal denoising by our proposed method, we compared its performance on synthetic and field data using complete ensemble empirical mode decomposition (CEEMD) and synchro squeezed wavelet transform (SWT). The proposed method denoising performance is better than other two methods.