Compact Dual-Polarized Vivaldi Antenna for Ground Penetrating Radar (GPR) Application

由CUDA核函数与PyTorch混合编译加速的快速探地雷达双参数全波形反演方法

Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch

本研究提出一种由CUDA核函数与PyTorch混合编译加速的探地雷达双参数全波形反演框架，利用GPU编程实现介电常数和电导率的高效准确反演，具备高精度、灵活可扩展性，适用于快速地下成像。

Slice-Connection Clustering Algorithm for Tree Roots Recognition in Noisy 3D GPR Data

3D mapping of tree roots is a popular ground-penetrating radar (GPR) application. In real field tests, the recognition of tree roots suffers due to noisey reflection patterns from subsurface targets that are not of interest, such as rocks, cavities, soil unevenness, etc. A Slice-Connection Clustering Algorithm (SCC) is applied to separate the regions of interest from each other in a reconstructed 3D image. The proposed method can successfully recognize the radar signatures of the roots and distinguish roots from other objects. Meanwhile, most noise radar features are ignored through our method…

Dispersion Compensation of Sinuous Antennas for Ground Penetrating Radar Applications

Sinuous antennas exhibit many desirable properties for ground penetrating radar (GPR) applications such as ultra-wide bandwidth, polarization diversity, and a low-profile form factor. However, sinuous antennas are dispersive since the active region moves with frequency along the structure. This is an undesirable quality for pulsed-radar applications since the radiated pulse will be distorted. Such distortion may be detrimental to close-in sensing applications such as GPR. This distortion may be compensated in processing with accurately simulated or measured phase data. However, antenna perform…

基于机器学习的步进频率探地雷达现场测量土壤分析：初步研究

Soil analysis with machine-learning-based processing of stepped-frequency GPR field measurements: Preliminary study

本研究利用拖拉机搭载的空气耦合步进频率探地雷达结合机器学习，预测电磁感应仪测得的表观电导率，以评估其获取土壤参数的能力，并提出了块金值与基台值之比作为性能指标。

Accurate Tree Roots Positioning and Sizing over Undulated Ground Surfaces by Common Offset GPR Measurements

Tree roots detection is a popular application of the Ground-penetrating radar (GPR). Normally, the ground surface above the tree roots is assumed to be flat, and standard processing methods based on hyperbolic fitting are applied to the hyperbolae reflection patterns of tree roots for detection purposes. When the surface of the land is undulating (not flat), these typical hyperbolic fitting methods becomes inaccurate. This is because, the reflection patterns change with the uneven ground surfaces. When the soil surface is not flat, it is inaccurate to use the peak point of an asymmetric reflec…

透明化浅层冰冻圈：基于无人机探地雷达的高分辨率地下成像——综述与展望

Transparentize A Shallow Cryosphere: High-Resolution Subsurface Imaging using UAV-Borne GPR A review and prospective

本文综述了无人机载探地雷达在浅层冰冻圈地下成像中的系统架构、操作策略和数据处理方法，并通过东南极莫愁湖案例验证了其高精度（冰厚误差0.03米），指出了未来挑战。

DMRF-UNet: A Two-Stage Deep Learning Scheme for GPR Data Inversion under Heterogeneous Soil Conditions

Traditional ground-penetrating radar (GPR) data inversion leverages iterative algorithms which suffer from high computation costs and low accuracy when applied to complex subsurface scenarios. Existing deep learning-based methods focus on the ideal homogeneous subsurface environments and ignore the interference due to clutters and noise in real-world heterogeneous environments. To address these issues, a two-stage deep neural network (DNN), called DMRF-UNet, is proposed to reconstruct the permittivity distributions of subsurface objects from GPR B-scans under heterogeneous soil conditions. In …

连接仿真与现实的地下雷达感知：基于物理的分层域适应与深度对抗学习

Bridging simulation and reality in subsurface radar-based sensing: physics-guided hierarchical domain adaptation with deep adversarial learning

本研究提出一种基于物理的分层域适应与深度对抗学习框架，用于提高地下材料属性估计的鲁棒性和准确性。

使用深度受限重建评分的探地雷达地下隧道无监督检测

Unsupervised Detection of Underground Tunnels in Ground-Penetrating Radar Using Depth-Restricted Reconstruction Scoring

研究利用探地雷达检测地下隧道，提出无监督检测管道，通过去噪卷积自动编码器学习正常地下结构，用重建误差标记隧道，核心贡献是深度受限top-k异常评分提升检测效果。