Nowadays, benefiting from its strong capability of nondestructive detection, the ground-penetrating radar (GPR) has been applied to detect and reconstruct underground targets and has drawn lots of attention both in military and civilian fields. However, in the processing of GPR imaging, due to the dispersion errors caused by random distribution of various particles in soil, conventional imaging methods have disadvantages of low signal-noise ratio (SNR), low resolution, and unbalanced amplitude. In this article, to achieve high resolution and high veracity on underground targets’ 3-D reconstruction, we improved the conventional reverse time migration (RTM) algorithm in perspective of medium constitutive relationship. Besides, we extended the improved RTM method in 3-D environments and reconstructed the 3-D structure of several underground targets. To make the RTM algorithm suitable for stepped frequency continuous wave (SFCW) GPR system, we generated three excitation signal models and analyzed the effect of different excitation signals on imaging performance. Finally, through the quantitative analysis of simulation and on-vehicle experimental results, we found that the 3-D images generated by improved RTM method had higher resolution, smaller measurement error, and higher veracity than those of conventional RTM method.

中文翻译：

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一种新的基于 FDTD 的 3-D RTM 成像方法，用于在分散介质上工作的 GPR

如今，探地雷达（GPR）凭借其强大的无损探测能力，被应用于地下目标的探测和重建，在军事和民用领域引起了广泛关注。然而，在探地雷达成像的处理过程中，由于土壤中各种颗粒的随机分布造成的色散误差，传统的成像方法存在信噪比（SNR）低、分辨率低、幅度不平衡等缺点。本文为实现地下目标三维重建的高分辨率和高精度，从介质本构关系的角度改进了传统的逆时偏移（RTM）算法。此外，我们在 3-D 环境中扩展了改进的 RTM 方法，并重建了几个地下目标的 3-D 结构。为了使RTM算法适用于步进频率连续波（SFCW）探地雷达系统，我们生成了三个激励信号模型，并分析了不同激励信号对成像性能的影响。最后，通过仿真和车载实验结果的定量分析，我们发现改进的RTM方法生成的3D图像比传统的RTM方法具有更高的分辨率、更小的测量误差和更高的准确性。