基于遗传算法的探地雷达层状介质参数反演算法

探地雷达因其无损性与高效性，逐渐成为道路检测、地下勘探等领域的有效探测手段，而探地雷达的传统厚度反演算法存在无法有效检测分层介质厚度、相对介电常数等参数的问题，具有较大的多层介质参数反演误差。因此，本文提出了一种基于遗传算法的层状介质参数反演算法。算法从时域角度出发，结合共中心点方法，设计了基于遗传算法的优化模型，反演地下层状介质结构的参数信息。通过实验仿真，本文所提方法可以应用于地下多层介质，较为准确的反演出层状介质参数信息。 

Inversion algorithm for parameters of layered media with ground penetrating radar based on genetic algorithm

Because of its nondestructive and high efficiency, GPR has gradually become an effective detection method in the fields of road detection and underground exploration. However, the traditional GPR thickness inversion algorithm cannot effectively detect parameters such as thickness and relative dielectric constant of layered media, and has a large inversion error of multi-layer media parameters. Therefore, an optimization algorithm based on layered media parameters inversion algorithm is proposed in this paper. From the perspective of time domain, one optimization model based on genetic algorithm were designed with the common middle point method to retrieve the parameter information of underground layered media structure. Through experimental simulation, the method proposed in this paper can be applied to underground multilayered medium, and accurately invert the parameter information of layered medium.