A Fast-Autofocusing Approach for Ground Penetrating Radar Imaging Based on Correlation of Wavefield

The traditional migration imaging algorithms for ground penetrating radar have the disadvantages of high computational complexity and low accuracy, and require the accurate value of medium parameters. In this paper, a fast-autofocusing approach for ground penetrating radar imaging, based on correlation of wavefield, was proposed to solve these problems. The spectrum Green’s function and fast Fourier transform were employed to formulate the algorithm, which greatly saves the calculation and storage resources and makes it possible to perform real-time and high-resolution imaging for underground targets. Furthermore, by introducing a time phase factor into the imaging formula, a series of images at different focusing time were obtained and then the optimal focused image was stored as the output based on the minimum entropy criterion, which solved the problem of smearing and blurring of the image caused by incorrect estimation of the medium parameters. Simulation results verified that the proposed algorithm can provide high-quality autofocusing image regardless of the estimated value of the medium parameters.