Joint Calibration Algorithm of Extrinsic Parameters of LiDAR-INS for Unmanned Surface Vehicle

In this paper, a joint calibration method of LiDAR-INS extrinsic parameters based on the least square iterative algorithm is proposed to meet the challenges of sensor calibration under complex dynamic conditions in water surface environment. Traditional calibration methods are mostly used in land environment, and it is difficult to deal with the impact of water wave reflection, refraction and environmental noise on lidar data. Combined with the Beidou satellite positioning and timing system, this paper optimizes the space and time synchronization between sensors through the improved point cloud filtering strategy and the least square method. The experimental results show that this method can effectively achieve the extrinsic parameter calibration between lidar and INS, improve the overall accuracy and point cloud quality of the USV sensing system, and is of great significance to improve the autonomous navigation ability of the USV.