Laser Beam Profile Gaussian Approximation Algorithms Based On Robust Estimation

During the gaussian approximation of laser beam profile, the least squares fitting method is used as a general core algorithm. But the least squares fitting method is sensitive to abnormal data, the data acquisition process of noise can seriously affect the fitting goodness of the least squares method and affect accurcy of the gaussian approximation. For the lack of robust ability of least squares fitting method, the robust estimation is applied to the laser beam profile gaussian approximation algorithm, by the iteration of the algorithm and giving different weights to each observation data, makes the least squares fitting method has robust ability, which can overcome the influence of noise on the gaussian approximation accuracy. The experimental results show that the robust estimation methods, effectively improve the gaussian approximation accuracy of a laser beam profile, has important application value in the analysis of the laser beam quality.