Three-Dimensional Permittivity and Conductivity Imaging by Efficient Full Waveform Inversion of 3-D GPR Polarization Data Based on Random Source Strategy

作者：Xun Wang, Yi Qu, Lei Zhu, Deshan Feng, Siyuan Ding, Wentao Yuan, Bingchao Li, Tianxiao Yu · 发表于：IEEE Sensors Journal · 年份：2025 · DOI：10.1109/jsen.2025.3566147 · 被引用次数：7 · 研究领域：Geophysical Methods and Applications、Seismic Imaging and Inversion Techniques、Geophysical and Geoelectrical Methods

Three-dimensional ground penetrating radar (GPR) has gained widespread usage in shallow surface exploration due to its ease of acquisition and ability to capture diverse polarization information Meanwhile, the quantitative interpretation of 3D GPR data through Full Waveform Inversion (FWI), particularly when incorporating various polarization methods, holds substantial practical significance. Nonetheless, Challenges in 3D GPR FWI, including multiple solutions and high memory demands, limit its theoretical potential. In this study, we propose an efficient 3D frequency-domain FWI approach utilizing dual-parameter attributes applied to 3D GPR synthetic polarization data. First, we develop the algorithm, frequency weighting and gradient preconditioning strategies are adopted to reduce the nonlinearity and enhance deep illumination of inversion, and the random source strategy is used to improve the efficiency. Subsequently, we apply the algorithm to investigate different polarization data. Then, we use the algorithm to realize 3D multi-parameters quantitative imaging of GPR polarization data, and discuss the reconstruction characteristics of different polarization data, which makes 3D GPR FWI feasible. Our findings not only enhance the understanding of GPR data but also pave the way for more accurate and efficient subsurface exploration using GPR multi-polarization data.