Multi-Offset Synthetic GPR Data

<b>Overview</b>This repository contains the data and scripts related to the paper titled "A realistic 2D multi-offset, multi-frequency synthetic GPR data set as a benchmark for testing new algorithms" The data set includes synthetic GPR data generated using gprMax, detailed descriptions of the acquisition geometry, and the required Conda environment for running the associated Jupyter notebooks.<br><b>Repository Contents</b><br>- <code>env.yml</code> Conda environment file listing all dependencies required to run the Jupyter notebooks.- <code>notebooks</code> Directory containing Jupyter notebooks to open and validate the data files.- <code>data</code> Directory containing the synthetic GPR data files.<br><br><b>GPR Data</b>The synthetic GPR data set was generated using the gprMax software, which simulates electromagnetic wave propagation using the Finite-Difference Time-Domain (FDTD) method. The data set includes multiple 2D profiles with varying offsets and frequencies, designed to test and evaluate processing, analysis, and inversion routines for GPR data.<b>Acquisition Geometry</b>For each of the four sections selected within the model, 161 shots and 161 receivers were used, covering different frequencies (50 MHz, 100 MHz, and 200 MHz). Detailed sketches and validation methods are provided within the Jupyter notebooks.<br><b>Usage Notes</b>An example Python code to read the header file and additional usage notes can be found within the Jupyter notebooks provided in this repository.

<b>Overview</b>本仓库包含与题为《面向新型算法测试的基准合成2D多偏移距多频地面穿透雷达（Ground Penetrating Radar，GPR）数据集》（A realistic 2D multi-offset, multi-frequency synthetic GPR data set as a benchmark for testing new algorithms）的学术论文相关的数据与脚本。该数据集包含使用gprMax生成的合成GPR数据、采集几何的详细说明，以及运行配套Jupyter笔记本所需的Conda环境配置。<br><b>Repository Contents</b><br>- <code>env.yml</code>：用于运行Jupyter笔记本的全部依赖项清单的Conda环境配置文件。<br>- <code>notebooks</code>：存放用于打开并校验数据文件的Jupyter笔记本的目录。<br>- <code>data</code>：存放合成GPR数据文件的目录。<br><br><b>GPR Data</b>本合成GPR数据集基于gprMax软件生成，该软件通过时域有限差分（Finite-Difference Time-Domain，FDTD）方法模拟电磁波传播。数据集包含多组不同偏移距与频率的2D剖面，用于测试与评估GPR数据的处理、分析及反演流程。<br><b>Acquisition Geometry</b>针对模型中选取的4个区域，本次采集均使用161个激发点与161个接收点，覆盖50 MHz、100 MHz及200 MHz三种频率。Jupyter笔记本中提供了详细的示意图与校验方法。<br><b>Usage Notes</b>读取头文件的示例Python代码与额外使用说明均可在本仓库提供的Jupyter笔记本中获取。

搜集汇总

背景与挑战

背景概述

该数据集是一个合成的多偏移量、多频率GPR数据集，使用gprMax软件生成，包含多个2D剖面和详细的采集几何信息，旨在为测试新算法提供基准。数据集还提供了Jupyter notebooks和Conda环境文件，方便用户进行数据验证和分析。