Abstract
Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.
Highlights
light detection and ranging (LiDAR) scanning can acquire three-dimensional (3D) geo-spatial data accurately and efficiently, and has recently become one of the most important 3D geo-spatial data acquisition technologies
Differing to the planar feature or other features based boresight angle calibration methods, this paper proposes a boresight self-calibration method for mobile LiDAR scanning (MLS) systems and UAV LiDAR scanning (ULS) systems based on the point to point correspondences in overlapping strips matched by an Iterative Closest Point (ICP) algorithm
This paper deals with the boresight calibration of mobile LiDAR scanning systems and UVA LiDAR scanning systems
Summary
LiDAR (light detection and ranging) scanning can acquire three-dimensional (3D) geo-spatial data accurately and efficiently, and has recently become one of the most important 3D geo-spatial data acquisition technologies. To meet different geo-spatial data acquisition demands in different fields, LiDAR sensors are integrated in mobile LiDAR scanning (MLS) systems [1], airborne LiDAR scanning (ALS) systems [2], UAV LiDAR scanning (ULS) systems [3], and even personal LiDAR scanning (PLS) systems [4]. Owing to high pulse frequency of the LiDAR sensors and the ability of obtaining position and orientation of platform in real time by the equipped GNSS/IMU, both MLS systems and ULS systems can efficiently and directly acquire 3D geo-referenced spatial data. The existing of lever-arm offsets and boresight angles will affect the positioning accuracy of MLS systems and ULS systems severely [15]. Precise calibration of the lever-arm offsets and boresight angles of MLS systems and ULS systems is required
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