 This paper proposes a novel algorithm for separating ground and non-ground measurements from airborne LiDAR data. It uses a rigid cloth model to approximate the ground surface, allowing for easier parameterization and faster processing than other methods. The resulting ground points can then be extracted from the LiDAR point cloud using a comparison process. This algorithm has been validated on benchmark datasets provided by ISPRS Working Group 3-3, achieving an average total error of 4.58%. This makes it comparable to many existing state-of-the-art filtering algorithms. The proposed method is easy to use and could potentially make LiDAR data more accessible to those who do not have extensive experience or knowledge in the field. This article was authored by Wu Mingzhang, Jian Baqi, Peng Wan, and others.