Interface identification using a GPR signal: a Monte Carlo Markov chain approach

Abstract

This paper presents a new signal processing method to improve the identification of interface between different layered media, using a ground penetrating radar (GPR) recording. Our methodological approach is based on Monte Carlo Markov chain (MCMC) model. The deconvolution of the GPR signal is obtained in considering a stochastic estimation related to a maximum a posteriori criterion. The only known elements are the signal recorded from the GPR backscattering (one dimension approximation), and the order of the ARMA signal model for the emitted pulse.