基于LiDAR数据的布料模拟滤波算法的适用性分析

为了解决现有点云滤波算法设置参量多、滤波效果不理想、难以操作等问题，采用最新的布料模拟滤波算法，根据简单的物理过程构建虚拟格网模拟地形表面，并针对复杂地形的点云数据进行定性和定量滤波验证。结果表明，其Ⅰ类误差在5.7%、Ⅱ类误差在3.4%以内，但针对部分混合有平坦和陡坡的局部区域滤波效果并非理想；在满足滤波精度的同时，可在30s内完成数百万个点的滤波，甚至在数秒内完成数十万个点的滤波。该算法所需参量很少、效率非常高，能满足绝大多数复杂地形数据的滤波要求。

Applicability analysis of cloth simulation filtering algorithm based on LiDAR data

In order to solve the problems in the existing point cloud filtering algorithm, such as too many parameters, without ideal filtering effect and inconvenient operation, the cloth simulation filtering (CSF) algorithm was chosen to construct virtual grid to simulate terrain surface. The algorithm was verified using the qualitative and quantitative experiment and analysis in complex terrain point cloud data. The results show that type Ⅰ error is less than 5.7%, type Ⅱ error less than 3.4%, but for the local area with some mixed flat and steep slope the filtering effect is not ideal; The algorithm can achieve the filtering of millions of points in 30s while satisfying the filtering precision, and even hundreds of thousands of points in several seconds. The algorithm requires few parameters and is very efficient. It can satisfy the filtering requirements of most complex terrain data.