Sparse decomposition of the GPR useful signal from hyperbola dictionary

Abstract

In order to improve asset knowledge and avoid third part damages during road works, the localization of gas pipes in a non-destructive way has become a wide domain of research during these last years. The Ground Penetrating Radar (GPR) is used to detect buried gas pipes. However it does not directly provide a 3D position but a reflection map also called B-scan that the user must interpret. In order to facilitate the B-scan interpretation, we propose to use a dictionary of theoretical pipe signatures. One of the most popular method to compute the coefficients is the sparse coding. Nevertheless, clutter which is noticeable by its horizontal shape makes difficult to decompose it into sparse coefficients with this dictionary. Then a low-rank matrix constraint which models the clutter is applied in order to decompose the useful signal into sparse coefficients in a blind source separation framework. Our method has been applied to simulated and real data acquired on a test area. The proposed method presents satisfying qualitative and quantitative results.