Rigorous Calibration of UAV-Based LiDAR Systems with Refinement of the Boresight Angles Using a Point-to-Plane Approach

Abstract

Advances in micro-electro-mechanical navigation systems and lightweight LIDAR (light detection and ranging) sensors onboard unmanned aerial vehicles (UAVs) provide the feasibility of deriving point clouds with very high and homogeneous point density. However, the deformations caused by numerous sources of errors should be carefully treated. This work presents a rigorous calibration of UAV-based LiDAR systems with refinement of the boresight angles using a point-to-plane approach. Our method is divided into a calibration and a parameter mounting refinement part. It starts with the estimation of the calibration parameters and then refines the boresight angles. The novel contribution of the paper is two-fold. First, we estimate the calibration parameters conditioning the centroid of a plane segmented to lie on its corresponding segmented plane without an additional surveying campaign. Second, we refine the boresight angles using a new point-to-plane model. The proposed method is evaluated by analyzing the accuracy assessment of the adjusted point cloud to point/planar features before and after the proposed method. Compared with the state-of-the-art method, our proposed method achieves better positional accuracy.