Two-parameter synchronous inversion method for three-dimensional frequency domain ground penetrating radar

Abstract

The invention discloses a two-parameter synchronous inversion method for a three-dimensional frequency domain ground penetrating radar. The method comprises the steps: inputting observation data, setting a three-dimensional initial model, and initializing parameters; performing forward modeling on the established three-dimensional initial model; constructing an inversion objective function, and decomposing the inversion objective function into two alternate sub-problems; initializing the dielectric constant and the conductivity to obtain an initial pilot model vector; solving a sub-problem 1 according to the pilot model vector, and updating a model medium parameter vector; solving a sub-problem 2 according to the obtained model medium parameter vector, and updating a pilot model vector; and updating synchronously and alternately until an inversion termination condition is met, and outputting an inversion result. According to the invention, the dielectric constant and the conductivity value can be updated synchronously, so that the inversion efficiency is improved; a total variation model constraint method is improved to a full waveform inversion process, and the robustness of an algorithm is increased; and a frequency weight factor is combined, and a parallel mode is adopted to realize 3D GPR quantitative imaging, so that the imaging process is more efficient and accurate.

Description

technical field [0001] The invention belongs to the field of geophysical detection, and in particular relates to a two-parameter synchronous inversion method of a ground-penetrating radar in a three-dimensional frequency domain. Background technique [0002] Ground penetrating radar (GPR) is an electromagnetic non-destructive detection technology for locating underground abnormal bodies, structures and characteristics, or invisible targets inside objects. In the actual GPR detection, the position, size and size of the detection target can be roughly inferred only by the obtained radar profile. However, bottom-penetrating radar is mostly limited to rough estimates, and it is still unable to give parameters such as permittivity and electrical conductivity of abnormal objects to achieve precise definition of target object attributes. Full waveform inversion (FWI) is a new and important imaging method. GPR full waveform inversion can obtain physical parameters such as dielectr...

AI Technical Summary

Problems solved by technology

Watson uses an approximate total variation regularization to constrain the permittivity model so that its inversion results have a sharp interface. This approximate total variation method may be unstable and the convergence of the inversion cannot be guaranteed

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