Full-waveform Inversion of Noisy GPR Data in Frequency Domain Based on Quasi-Newtonian Algorithm

Abstract Ground penetrating radar (GPR) is a non-destructive detection technology. Full-waveform inversion (FWI) of GPR data promise for the quantitative characterization of the earth’s shallow subsurface parameters, which is useful for the interpretation and subsurface mapping. In this paper, we present a full-waveform inversion target imaging framework for GPR. In the method, the singular value decomposition (SVD) and least squares (LS) methods are used to denoise the measured scattering field. Secondly, the contrast source inversion (CSI) method is improved by introducing the quasi-Newtonian algorithm. Theoretical analysis and practice show that the proposed method can improve the robustness and stability of the inversion, and finally achieve a result with lower contrast error.