Ground Penetrating Radar Signal Processing Based on Morphological Component Analysis

Ground-penetrating radar (GPR) is one of the most popular underground detection devices and has a wide range of applications. However, when using GPR to detect targets, since targets are located near the surface, the influence of clutter on target detection is very serious. Especially in some complex environments, targets may be completely covered by clutter. Thus, clutter reduction is the primary task. Singular value decomposition (SVD), principal component analysis (PCA) and independent component analysis (ICA) are commonly used for target detection. In this paper, a method based on morphological component analysis (MCA) is adopted, and a decomposition model is proposed to distinguish between target and clutter. Finally, it is proved by visual simulation that this method is superior to other methods in removing clutter.