Sparse signal decomposition for ground penetrating radar

In this paper, we present an adaptive approach for sparse signal decomposition, in which each GPR trace is decomposed into elementary waves automatically. A sparse feature vector is extracted from the decomposition and used for classification of railway ballast. The experimental results show that the proposed approach can represent the GPR signals efficiently, and effective features can be extracted for pattern classification.