School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
Sensors (Basel). 2023 Jan 11;23(2):852. doi: 10.3390/s23020852.
Building reconstruction using high-resolution satellite-based synthetic SAR tomography (TomoSAR) is of great importance in urban planning and city modeling applications. However, since the imaging mode of SAR is side-by-side, the TomoSAR point cloud of a single orbit cannot achieve a complete observation of buildings. It is difficult for existing methods to extract the same features, as well as to use the overlap rate to achieve the alignment of the homologous TomoSAR point cloud and the cross-source TomoSAR point cloud. Therefore, this paper proposes a robust alignment method for TomoSAR point clouds in urban areas. First, noise points and outlier points are filtered by statistical filtering, and density of projection point (DoPP)-based projection is used to extract TomoSAR building point clouds and obtain the facade points for subsequent calculations based on density clustering. Subsequently, coarse alignment of source and target point clouds was performed using principal component analysis (PCA). Lastly, the rotation and translation coefficients were calculated using the angle of the normal vector of the opposite facade of the building and the distance of the outer end of the facade projection. The experimental results verify the feasibility and robustness of the proposed method. For the homologous TomoSAR point cloud, the experimental results show that the average rotation error of the proposed method was less than 0.1°, and the average translation error was less than 0.25 m. The alignment accuracy of the cross-source TomoSAR point cloud was evaluated for the defined angle and distance, whose values were less than 0.2° and 0.25 m.
利用高分辨率星载合成孔径雷达层析成像（TomoSAR）进行建筑物重建，在城市规划和城市建模应用中具有重要意义。然而，由于 SAR 的成像模式是并排的，单个轨道的 TomoSAR 点云无法实现对建筑物的完整观测。现有的方法很难提取相同的特征，也很难利用重叠率来实现同源 TomoSAR 点云和异源 TomoSAR 点云的对齐。因此，本文提出了一种用于城市地区 TomoSAR 点云的稳健对齐方法。首先，通过统计滤波过滤噪声点和异常点，基于投影点密度（DoPP）的投影提取 TomoSAR 建筑物点云，并根据密度聚类获得后续计算所需的立面点。然后，使用主成分分析（PCA）对源点云和目标点云进行粗对齐。最后，利用建筑物对立面法向量的角度和立面投影外端的距离计算旋转和平移系数。实验结果验证了所提出方法的可行性和稳健性。对于同源 TomoSAR 点云，实验结果表明，所提出方法的平均旋转误差小于 0.1°，平均平移误差小于 0.25 m。对于定义的角度和距离，评估了异源 TomoSAR 点云的对齐精度，其值小于 0.2°和 0.25 m。
