探地雷达多阶段级联U-Net墙内小目标三维重建方法  

Three-dimensional Reconstruction Method for Detecting Small Targets within Walls Based on a Multistage Cascade U-Net Approach Using Ground Penetrating Radars

作　　者：兰天 盛世文 孙熙韬 高炜程 杨小鹏 LAN Tian;SHENG Shiwen;SUN Xitao;GAO Weicheng;YANG Xiaopeng(Beijing Institute of Technology Chongqing Innovation Center,Chongqing 401120,China;School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China;Chongqing Key Laboratory of Novel Civilian Radar,Chongqing 401120,China)

机构地区：[1]北京理工大学重庆创新中心,重庆401120 [2]北京理工大学信息与电子学院,北京100081 [3]新体制民用雷达重庆市重点实验室,重庆401120

出　　处：《雷达学报（中英文）》2024年第6期1184-1201,共18页Journal of Radars

基　　金：国家自然科学基金(62471037,62101042);中央高校基本科研业务费专项资金(XSQD-6120220083)。

摘　　要：探地雷达(GPR)在对掩埋目标的探测中发挥着至关重要的作用,尤其在墙体内小目标检测及重建方面。由于墙体结构及材质的复杂性,墙内小目标精准重建面临极大挑战。针对墙内小目标重建难题,该文提出了一种多阶段级联U-Net方法,用于墙内小目标的三维重建。首先,通过蒙特卡罗抽样生成符合级配要求的物理三维骨料散射模型,构建了复杂墙体场景的高分辨率探测模型和数据集,以提高模拟的真实性和准确性;其次,多阶段网络结构的设计能够有效抑制C扫描数据中的噪声和非均质杂波,从而提升信号质量;最后,预处理后的数据用于重建小目标三维分布。此外,该文还引入了一种自适应多尺度模块和级联网络训练策略,优化了复杂场景中小目标信息的拟合性能。通过模拟与实测数据的对比,验证所提方法的有效性和泛化能力。相比现有技术,该方法成功重建了三维墙体内小目标,显著提高了峰值信噪比,为小目标的准确探测提供了重要技术支持。Ground Penetrating radars(GPR)are essential for detecting buried targets in civilian and military applications,especially given the increasing demand for detecting and imaging small targets within walls.The complex structures and materials of walls pose substantial challenges for precisely reconstructing small targets.To address this issue,this study proposes a multistage cascaded U-Net approach for the three-dimensional reconstruction of small targets within walls.First,we developed a high-resolution detection model and a dataset tailored to handle complex wall scenes.Thereafter,using the Monte Carlo sampling method,we sampled aggregate particle sizes to create a physical three-dimensional aggregate scattering model that satisfies grading requirements,thus enhancing the realism and accuracy of the simulated scenes.Our multistage network design effectively suppresses noise and inhomogeneous clutter in C-scan data,thereby improving signal quality.The preprocessed data are then fed into subsequent network stages to reconstruct the distribution of three-dimensional reconstruction values.In addition,we proposed an adaptive multiscale module and a cascaded network training strategy to better fit small target information in complex scenes.Through comparisons with simulated and measured data,we confirmed the effectiveness and generalizability of our method.Unlike existing techniques,our approach successfully reconstructs small targets within three-dimensional walls,thereby considerably enhancing the peak signal-to-noise ratio and providing critical technical support for accurately detecting small targets within walls.

关 键 词：探地雷达 墙内小目标 三维重建 杂波抑制 级联U-Net网络 

分 类 号：TN959[电子电信—信号与信息处理]