With the rapid expansion of urban areas and the increasing use of electricity, the need for locating buried cables is becoming urgent. In this article, a novel method to locate underground cables based on ground penetrating radar (GPR) and Gaussian-process regression is proposed. First, the coordinate system of the detected area is conducted, and the input and output of locating buried cables are determined. The GPR is moved along the established parallel detection lines, and the hyperbolic signatures generated by buried cables are identified and fit, thus the positions and depths of some points on the cable could be derived. On the basis of the established coordinate system and the derived points on the cable, the clustering method and cable fitting algorithm based on Gaussian-process regression are proposed to find the most likely locations of the underground cables. Furthermore, the confidence intervals of the cables’ locations are also obtained. Both the position and depth noises are taken into account in our method, ensuring robustness in different environments and equipment. Experiments on real-world datasets are conducted, and the obtained results demonstrate the effectiveness of the proposed method.

中文翻译：

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通过探地雷达和高斯过程回归绘制埋地电缆图


随着城市面积的快速扩张和电力使用量的不断增加，对埋地电缆进行定位的需求变得日益迫切。在本文中，提出了一种基于探地雷达（GPR）和高斯过程回归的地下电缆定位新方法。首先建立检测区域的坐标系，确定埋地电缆定位的输入和输出。探地雷达沿着建立的平行探测线移动，识别并拟合埋地电缆产生的双曲线特征，从而推导出电缆上某些点的位置和深度。在建立的坐标系和电缆上导出的点的基础上，提出了基于高斯过程回归的聚类方法和电缆拟合算法，以找到地下电缆最有可能的位置。此外，还获得了电缆位置的置信区间。我们的方法考虑了位置和深度噪声，确保了不同环境和设备的鲁棒性。在真实数据集上进行了实验，获得的结果证明了该方法的有效性。