Modeling and Simulation of Camera Positioning Stance on the Basis of Different Error Sources

High-definition (HD) cameras and Light Detection and Ranging (LiDAR) are used for foreign object identification and volume alarm provision on coal transport lines, and improving the accuracy of jointly calibrated HD camera and LiDAR data is essential.To determine the effect of errors on camera parameters through the classical image backward rendezvous model, this study proposed an evaluation model for the error sources in backward rendezvous.Positioning accuracy was analyzed by assuming the existence of systematic errors in camera principal distance and image principal point offset and the presence of random errors in the image point and LiDAR point cloud coordinates.The accuracy of the computational model was verified through experiments.Results demonstrate that, the positioning accuracies are -23.2mm 17.4 mm, -20.6 mm 17.5 mm, and -2.9 mm 19.6 mm at a given random error of 0.02 m in the control point and at an error of 1 pixel in the image point.Increasing the control point improved the accuracy of camera positioning.The systematic errors in the camera's principal distance and in the image point coordinates affect the accuracy of positioning.This study provides a theoretical basis for the joint calibration of HD cameras and LiDAR, which is crucial for improving the accuracy of foreign object identification and volume alarm functions in coal transport lines.