Layered-medium time delay estimation of GPR returns based on sparsity constraint

In this paper, we propose a novel adaptive sparse decomposition method which transforms the classical parameter estimation problem into a dictionary learning problem for ground penetrating radar(GPR) signal time delay estimation(TDE). In comparison with traditional subspace-based methods, our algorithm estimates radar signal time delay by choosing a few atoms from an over-complete dictionary which improves the TDE accuracy rate when signal-to-noise ratio(SNR) is low and reduces the computational complexity.