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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Terrain Point Cloud Assisted GB-InSAR Slope and Pavement Deformation Differentiate Method in an Open-Pit Mine
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Terrain Point Cloud Assisted GB-InSAR Slope and Pavement Deformation Differentiate Method in an Open-Pit Mine

机译：露天矿中地形点云辅助的GB-InSAR边坡与路面变形微分方法

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摘要

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.
机译：地面合成孔径雷达干涉仪（GB-InSAR）是用于变形监测的有价值的工具。通过GB-InSAR获得的2D干涉图可以与3D地形模型集成，以视觉和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。但是，由于视线（LOS）变形监测，阴影和下垂经常发生在地形崎ged的区域，这使得很难区分斜坡上的变形点和人行道上的变形点。为解决点云和雷达像素之间的比例差异而设计的现存重采样和插值方法没有考虑坡度的局部散射特性差异。地形模型中路面和坡面的散射差异信息被大大削弱。我们提出了一种集成了GB-InSAR和地形表面点云的差异化方法。提取了边坡的局部几何特征和散射特征，解释了路面和边坡的差异。几何模型基于具有线性重复通过和地形点云相对观测几何形状的GB-InSAR系统。散射模型基于小补丁中的k最近邻（KNN）点，其随雷达微波入射角的变化而变化。在露天矿中进行了模拟和现场实验。结果表明，该方法能有效地区分路面和坡面变形，并消除了异常区域边界。

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