Research on adaptive clutter suppression for ground penetrating radar based on wavelet transform and K-SVD - Xueli WU (Hebei University of Science and Technology, 2021)
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.