基于小波自适应阈值方法的探地雷达去噪

探地雷达在实际使用过程中会被各种噪音信号干扰，针对这一问题，本文提出一种基于小波自适应阈值算法的探地雷达信号处理方法。常规小波阈值算法处理探地雷达B-scan图像时因处理前后的小波系数有所差异，可能导致图像失真。为了使目标信号更加明确，并消除噪音等干扰，通过对小波阈值的选取方式和阈值函数进行改进，使用小波变换的不同层数的子带长度确定阈值，实现阈值自适应准确量化。实验结果表明该方法相对传统小波阈值算法更加适用于探地雷达信号处理，自适应阈值函数拥有更好的良好连续性和稳定性，进一步提高了去除直达波和降噪效果，更好的保存了目标图像的细节。与其他方法对比结果表明，本文提出的算法提高了峰值信噪比，降低了图像熵。可见该方法在探地雷达实际使用情况下有一定的应用价值。

Research on clutter suppression for ground-penetrating radar based on wavelet adaptive thresholding method

Ground-penetrating radar will be disturbed by various noise signals in the actual use process, and to solve this problem, this paper proposes a Ground-penetrating radar denoising based on wavelet adaptive thresholding method. Conventional wavelet thresholding algorithms for ground-penetrating radar B-scan images may cause image distortion due to the difference in wavelet coefficients before and after processing. In order to make the target signal clearer and eliminate interference such as noise, wavelet thresholds are improved by the way of selecting wavelet thresholds and the threshold function, and the thresholds are identified with the length of sub-bands of different layers of wavelet transform to achieve adaptive and accurate quantization of thresholds. The experimental results show that the method is applicable to ground-penetrating radar signal processing and improves the good continuity and stability of the threshold function compared with the ordinary wavelet thresholding algorithm, further improves the direct wave removal and noise reduction effects, and better preserves the details of the target image. Comparing the results with other methods shows that the algorithm proposed in this paper improves the peak signal-to-noise ratio and reduces the image entropy. The research results show that the method has a certain application value in the practical use case of ground-penetrating radar.