Research On Joint Calibration Algorithm In Active And Passive Pose Measurement System

With the development of measurement technology,it is increasingly difficult for a single measurement sensor to meet the needs of high-precision measurement tasks.The integration of multi-sensor measurement data can take advantage of various types of sensors,and is a development trend for achieving high-precision measurement tasks.Interferometric Synthetic Aperture Radar(SAR)is a popular remote sensing technology in recent years.The relative motion between radar antennas has a serious impact on measurement accuracy.Therefore,a measurement system is needed to measure the pose relationship between antennas in real time.The pose measurement system in this subject uses a fusion measurement scheme of active laser ranging sensor and passive vision sensor.In this paper,the joint calibration technology between active laser ranging sensor and passive vision sensor is explored.The measurement model based on active laser ranging sensor and visual sensor is established.The laser spot and camera calibration plate in joint calibration are analyzed.Image feature point extraction method is proposed,and a joint calibration algorithm between active laser ranging sensor and passive vision sensor is proposed.Firstly,based on the in-depth research on the development of camera calibration and one-dimensional laser calibration method,the paper analyzes the principle of camera calibration and laser range finder,and establishes the pinhole imaging model and laser measurement model which introduce the camera distortion model.Based on the camera imaging model,the laser measurement model is unified into the camera coordinate system by analyzing the distribution of the laser spot and the pose representation of the laser beam in three-dimensional space and the mutual transformation between the coordinate systems in three-dimensional space.A measurement model combining laser ranging sensor and visual sensor is established,which lays a solid theoretical foundation for joint calibration between laser range finder and camera.Then,in order to link the two-dimensional image coordinates of the feature points in the passive vision measurement with the three-dimensional coordinates in the real world,the image feature point extraction method is studied,including the corner point extraction algorithm and the centroid extraction algorithm.The Harris corner extraction algorithm and Bouguet sub-pixel corner extraction method are studied.The advantages of Bouguet algorithm to Harris algorithm are analyzed by the comparison of the board based on the checkerboard calibration.Based on the analysis of the distribution of laser spot,the principles of gray-weighted centroid method and Gaussian function fitting method are studied respectively.The simulation results are generated by experiments,and the advantages and disadvantages of the two algorithms are compared and analyzed.Finally,the joint calibration algorithm for multi-sensor fusion is studied and analyzed.The camera calibration algorithm and the laser range finder calibration algorithm are separately studied.Based on the camera calibration algorithm,the measurement model of the laser range finder is converted into the camera imaging model,thereby achieving joint calibration between the laser ranging sensor and the camera.Aiming at the camera calibration algorithm,based on the research of Zhang Zhengyou calibration method,a single linear calibration method based on three-dimensional calibration plate is proposed.According to the RANSAC spatial point fitting algorithm,the laser beam is obtained.The relationship between the camera coordinate system and the laser ranging sensor coordinate system is used to unify the laser beam into the camera coordinate system to determine the laser center,thereby realizing the joint between the laser range finder and the camera.Calibration.Finally,the active and passive attitude measurement system consisting of laser range finder and monocular camera was built.The software was used to collect the actual measurement data.The data was used to complete the joint calibration experiment,which verified the feasibility and effectiveness of the proposed joint calibration algorithm.