System Self-Calibration Model for Non-Vertical Four-Prism Airborne LiDAR

Abstract

ABSTRACTSystem errors in light detection and ranging (LiDAR) systems cannot be ignored due to their influence on geo-referencing accuracy. Previous calibration methods are based on the vertical LiDAR system and do not simultaneously consider the bore-sight angles, lever-arm errors, angles, range, trajectory position, and angle correction parameters for each strip. This study proposes a system self-calibration model based on a high-precision positioning model for the non-vertical four-prism airborne LiDAR system. Furthermore, an automatic system calibration process is presented using this model that identifies 12 parameters for overlapping LiDAR data. Also, each strip of trajectory data has three position corrections and three angle corrections. The feasibility and applicability of the method is demonstrated via qualitative and quantitative analyses using real data from plain and hilly areas. The experimental results prove that the proposed method is stable and reliable. Specifically, the proposed method can compensate for system bias, correct original flight data, and provide seamless data. This model can be applied to actual flight engineering datasets, has no terrain limitations, no specific requirements for the trajectory configuration, no specific hypotheses, and no need for control information.