论文标题
通过地面穿透雷达和高斯过程回归绘制埋藏的电缆
Mapping the Buried Cable by Ground Penetrating Radar and Gaussian-Process Regression
论文作者
论文摘要
随着城市地区的迅速扩张和越来越多的电力利用，定位埋藏电缆的需求变得紧迫。在本文中，提出了一种基于地下电缆基于地下电缆（GPR）和高斯过程回归的方法。首先，进行检测区域的坐标系，并确定定位埋藏电缆的输入和输出。 GPR沿已建立的并行检测线移动，并鉴定并安装了由埋入电缆生成的双曲线特征，因此可以得出电缆上某些点的位置和深度。根据已建立的坐标系和电缆上的派生点，提议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。位置和深度噪声都在我们的方法中考虑到，以确保不同环境和设备的稳健性和可行性。进行了现实世界数据集的实验，所获得的结果证明了该方法的有效性。
With the rapid expansion of urban areas and the increasingly use of electricity, the need for locating buried cables is becoming urgent. In this paper, a noval method to locate underground cables based on Ground Penetrating Radar (GPR) and Gaussian-process regression is proposed. Firstly, 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 fitted, 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 cable's locations are also obtained. Both the position and depth noises are taken into account in our method, ensuring the robustness and feasibility in different environments and equipments. Experiments on real-world datasets are conducted, and the obtained results demonstrate the effectiveness of the proposed method.
