基于遗传算法的探地雷达层状介质参数反演算法

Renjie Liu, Tian Lan, Xiaopeng Yang, Yixuan Li

科研成果: 期刊稿件文章同行评审

4 引用 (Scopus)

摘要

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.

投稿的翻译标题Inversion Algorithm for Parameters of Layered Media with Ground Penetrating Radar Based on Genetic Algorithm
源语言繁体中文
页(从-至)2164-2170
页数7
期刊Journal of Signal Processing
37
11
DOI
出版状态已出版 - 11月 2021

关键词

  • common middle point
  • genetic algorithm
  • ground penetrating radar
  • layered media
  • parameter inversion

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