In this thesis, several aspects of GPR data processing for RC bridge decks are studied. First, autofocusing techniques are proposed to replace the previous expensive and unreliable human visual inspections during the iterative migration process for the estimation of the velocity/dielectric permittivity distribution from GPR data. Second, F-K filtering with dip relaxation is proposed for interference removal that is important for both imaging and the performance of post-processing techniques including autofocusing techniques and CS-based migration studied in this thesis. The targeted interferes here are direct waves and cross rebar reflections. The introduced dip relaxation is for accommodating surface roughness and medium inhomogeneity. Third, the newly developed CS-based migration is modified and evaluated on GPR data from RC bridge decks. A more accurate model by accounting for impulse waveform distortion that leads to less modeling errors is proposed. The impact of the selection of the regularization parameter on the comparative amplitude reservation and the imaging performance is also investigated, and an approach to preserve the comparative amplitude information while still maintaining a clear image is proposed. Moreover, the potential of initially sampling the time-spatial data with uniform sampling rates lower than that required by traditional migration methods is evaluated.