Abstract: Utilizing laser and camera for track geometry inspection, calibration approach for laser photogrammetric transducers is a key issue. The calibration models constructed by the nonlinear least-square method and Gaussian-Newton optimization computational method are presented respectively. The transducer measurement models parameters are acquired by the above-mentioned approaches making use of 200 individual data in the checkerboard plane by the dedicated test platform. Moreover, the other 200 individual data are added for different algorithms calibration errors analysis. The experimental results show that Gaussian-Newton algorithm is more accurate than the nonlinear least-square algorithm in camera calibration. The horizontal and vertical accuracy can improve 1.55 mm and 1.50 mm by use of Gaussian-Newton algorithm. While using laser photogrammetric transducers in track inspection vehicle, Gaussian-Newton calibration algorithm is proposed. Track gauge and bogie tilting angle computational formulations are given by Gaussian-Newton algorithm in the track inspection system.

Key words: Calibration, Camera, Laser, Track inspection