Dynamic calibration and compensation of a 3D laser radar scanning system

LIDAR (laser radar) is used to measure three-dimensional (3-D) object positions. It produces a range and an intensity image of the measured object and relies on the range image to determine the 3-D positions of the object. Because the range image is frequently corrupted with noise, a dynamic method to improve the LIDAR accuracy, based on a polynomial calibration model and an autoregressive moving-average calibration model, has been established. Experimental results show that the measurement errors of the LIDAR system have been reduced from 163 counts to 18 counts after compensation using the polynomial calibration model and that the errors have been further reduced to 11 counts with the ARMA model