Zheng Xiangtian, He Xiufeng, Yang Xiaolin, Ma Haitao, Yu Zhengxing, Ren Guiwen, Li Jiang, Zhang Hao, Zhang Jinsong
School of Earth Science and Engineering, Hohai University, Nanjing 211100, China.
China Academy of Safety Science and Technology, Beijing 100012, China.
Sensors (Basel). 2020 Apr 20;20(8):2337. doi: 10.3390/s20082337.
Ground-based synthetic aperture radar interferometry (GB-InSAR) is a valuable tool for deformation monitoring. The 2D interferograms obtained by GB-InSAR can be integrated with a 3D terrain model to visually and accurately locate deformed areas. The process has been preliminarily realized by geometric mapping assisted by terrestrial laser scanning (TLS). However, due to the line-of-sight (LOS) deformation monitoring, shadow and layover often occur in topographically rugged areas, which makes it difficult to distinguish the deformed points on the slope between the ones on the pavement. The extant resampling and interpolation method, which is designed for solving the scale difference between the point cloud and radar pixels, does not consider the local scattering characteristics difference of slope. The scattering difference information of road surface and slope surface in the terrain model is deeply weakened. We propose a differentiated method with integrated GB-InSAR and terrain surface point cloud. Local geometric and scattering characteristics of the slope were extracted, which account for pavement and slope differentiating. The geometric model is based on a GB-InSAR system with linear repeated-pass and the topographic point cloud relative observation geometry. The scattering model is based on k-nearest neighbor (KNN) points in small patches varies as radar micro-wave incident angle changes. Simulation and a field experiment were conducted in an open-pit mine. The results show that the proposed method effectively distinguishes pavement and slope surface deformation and the abnormal area boundary is partially relieved.
地基合成孔径雷达干涉测量技术（GB-InSAR）是一种用于变形监测的重要工具。GB-InSAR获取的二维干涉图可与三维地形模型相结合，以直观且准确地定位变形区域。该过程已通过地面激光扫描（TLS）辅助的几何映射初步实现。然而，由于视线（LOS）变形监测，在地形崎岖的区域经常会出现阴影和叠掩现象，这使得区分斜坡上的变形点和路面上的变形点变得困难。现有的重采样和插值方法是为解决点云与雷达像素之间的尺度差异而设计的，并未考虑斜坡的局部散射特性差异。地形模型中路面和斜坡表面的散射差异信息被大大削弱。我们提出了一种将GB-InSAR与地形表面点云相结合的差异化方法。提取了斜坡的局部几何和散射特征，用于区分路面和斜坡。几何模型基于具有线性重复轨道的GB-InSAR系统和地形点云相对观测几何。散射模型基于小区域内的k近邻（KNN）点随雷达微波入射角变化的情况。在一个露天矿进行了模拟和现场实验。结果表明，所提出的方法有效地区分了路面和斜坡表面的变形，并且部分缓解了异常区域边界问题。
