Modeling and analysis of light detection and ranging point cloud error in vibration state of airborne platform

Abstract

Airborne light detection and ranging (LiDAR) is frequently influenced by multiple positioning errors when converting laser echo signals into three-dimensional geospatial data. We focus on the error factor of airborne platform vibration, and analysis of the influence of platform instability on the output point cloud data by simulation, so as to correct it in the subsequent work. First, the influence of LiDAR attitude change on the formation of point cloud was analyzed from the airborne LiDAR geo-location equation. Then, the fluid characteristics of airborne platform in hovering state were obtained by simulation, and the vibration transfer relationship between airborne platform and LiDAR and the vibration model of LiDAR system were obtained based on the dynamic model, which was built on the flexible connection between airborne platform and LiDAR. Finally, we coupled the above vibration model with the airborne LiDAR geo-location equation and conducted a simulation to evaluate its effect on point cloud generation in a LiDAR system. The simulation results show that in the 100-m hovering state, the point cloud error caused by unmanned aerospace vehicle vibration can reach 200 and 400 mm in the horizontal and vertical directions, respectively. Moreover, due to the high vibration frequency, this error factor will also lead to the distortion of point cloud image, which will affect the subsequent point cloud data recognition.