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

Area of Science:

• Geomatics Engineering
• Robotics and Automation
• Remote Sensing

Background:

• Unmanned aerial vehicles (UAVs) equipped with micro-electro-mechanical navigation systems and light detection and ranging (LiDAR) sensors enable high-density point cloud generation.
• Systematic and random errors in UAV-based LiDAR data can lead to deformations, necessitating rigorous calibration procedures.

Purpose of the Study:

• To present a rigorous calibration method for UAV-based LiDAR systems, focusing on refining boresight angles.
• To improve the positional accuracy of point clouds derived from UAV-based LiDAR data.

Main Methods:

• A two-part method involving initial calibration parameter estimation and subsequent refinement of boresight angles.
• Utilizing a point-to-plane approach for boresight angle refinement.
• Estimating calibration parameters by ensuring segmented plane centroids align with their corresponding planes, without requiring additional surveying.

Main Results:

• The proposed method successfully refines boresight angles and improves the accuracy of the point cloud.
• Accuracy assessment shows enhanced alignment of the adjusted point cloud with point and planar features.
• The method achieves superior positional accuracy compared to existing state-of-the-art techniques.

Conclusions:

• The developed calibration method offers a robust solution for enhancing the accuracy of UAV-based LiDAR systems.
• The point-to-plane approach for boresight refinement is effective in mitigating deformations and improving data quality.
• This work contributes to more reliable and accurate geospatial data acquisition using UAVs.