基于波场互相关的探地雷达快速自聚焦成像

传统探地雷达偏移成像算法计算复杂度高、准确性低，且需要准确已知介质的电性参数。针对这些问题，本文提出了一种基于波场互相关的探地雷达快速自聚焦成像算法，利用水平分层介质频域格林函数的平移不变特性和快速傅里叶变换减小了对计算和存储资源的需求，并能够实时对地下目标进行高分辨成像；通过引入时间相位因子得到不同聚焦时刻的偏移图像，然后基于图像熵最小准则获取最优成像结果，解决了由于介质参数未知而导致的图像散焦问题。仿真结果验证了所提算法在介质参数未知情况下具有良好的自聚焦性能。 

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.