基于小波变换和K-SVD的探地雷达杂波抑制研究

Research on adaptive clutter suppression for ground penetrating radar based on wavelet transform and K-SVD

针对探地雷达原始图像中存在着大量以地表直达波为主的杂波噪声干扰问题,为了有效提取目标信号,提出了一种基于小波变换和K-Means奇异值分解的自适应双边滤波方法。将原始雷达数据进行小波分解,并应用K-SVD算法变换稀疏编码和更新原子,用更新后的稀疏系数和字典重构小块,将小块进行小波逆变换重构图像,然后对重构图像进行自适应双边滤波得到处理后的图像,以实现小波变换、K-SVD算法和自适应双边滤波方法的优势互补。与其他方法进行对比的结果表明,所提出的方法具有良好的杂波抑制效果,在峰值信噪比和目标图像熵上性能更好。研究结果在实际雷达勘测任务中具有一定的应用价值。

Aiming at the large amount of clutter and noise interference(mainly direct waves on the surface)in the original image of ground penetrating radar,an adaptive bilateral filtering method based on wavelet transform and K-Means singular value decomposition was proposed in order to effectively extract the target signal.The original radar data was decomposed by wavelet,and then the decomposed data was sparsely coded by K-SVD transform and updated atoms.The updated sparse coefficients and dictionary were used to reconstruct small blocks,and the small blocks were subjected to inverse wavelet transform to reconstruct the image.The reconstructed image was processed by adaptive bilateral filtering to obtain the processed image,so as to realize the complementary advantages of wavelet transform,K-SVD algorithm and adaptive bilateral filtering method.Compared with other methods,the experimental results show that the proposed method has a good clutter suppression effect and better performance in peak signal-to-noise ratio and target image entropy.The research results have certain application value in the actual radar survey tasks.