曲率分析的变分辨率数字高程模型建模算法

传统的数字高程模型一般采用规则网格划分以简化建模过程,因其网格密度缺乏对地形变化的自适应性而不能兼顾地形表达的准确度和地形数据的冗余度,导致其在车辆动力学仿真等领域的应用有所局限。针对这一问题提出一种基于曲率分析的随机节点分布建模方法,其数据节点的密度根据种子节点周围的局域曲面曲率变化而相应变化,实现了在复杂、曲率较大的地形区域自动生成高分辨率数字节点集,而在平缓、曲率较小的区域实现低分辨率的节点分布。在获得此种节点集的基础上,利用Delaunay三角剖分结合三次多项式插值算法,得到满足高精度和低数据冗余度的变分辨率数字高程模型。利用传统规则网格地形模型与所提出的变分辨率数字高程模型对同一个用于星球车动力学仿真的复杂野外地形进行对比,验证了变分辨率算法的有效性。

Varying resolution digital elevation model with surface curvature analysis

DEM with regular grids simplifies the modeling and analyzing processes; However, it fails to adapt to different terrain shapes and it is hard to obtain high surface accuracy and small dataset in the meantime, which limits its application in areas such as vehicle dynamic simulation. To solve this problem, we propose a modeling method with varying data resolution. The node density varies according to the local surface curvature so that it ensures high data resolution around sharp changing areas and low data resolution around relatively flat area. Then delaunay gridding method together with cubic interpolation is applied to obtain a digital elevation model with high surface accuracy and small data size using the resulting irregular node set. The proposed method is testified with a complex terrain surface used in rover simulation, and compared with the traditional regular grid model, which verifies its advantages in achieving the two major objectives.