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>项目概述</b>本代码仓库包含与题为《面向新算法测试的真实2D多偏移距、多频率合成探地雷达（Ground Penetrating Radar, GPR）数据集》的论文相关的数据与脚本。本数据集涵盖使用gprMax生成的合成探地雷达数据、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。<br><b>仓库内容</b><br>- <code>env.yml</code> Conda环境配置文件，列出了运行Jupyter笔记本所需的全部依赖项。<br>- <code>notebooks</code> 目录，包含用于打开并验证数据文件的Jupyter笔记本。<br>- <code>data</code> 目录，存储合成探地雷达数据文件。<br><br><b>探地雷达数据</b>本合成探地雷达数据集使用gprMax软件生成，该软件基于时域有限差分（Finite-Difference Time-Domain, FDTD）方法模拟电磁波传播。本数据集包含多组不同偏移距与频率的2D剖面，旨在用于测试与评估探地雷达数据的处理、分析及反演例程。<br><b>采集几何参数</b>针对模型中选定的四个区域，分别使用161个激发点与161个接收点，覆盖50 MHz、100 MHz与200 MHz三种不同频率。Jupyter笔记本中提供了详细示意图与验证方法。<br><b>使用说明</b>读取头文件的示例Python代码与其他使用说明，可在本仓库提供的Jupyter笔记本中获取。