Abstract
Non-uniform intensity distribution of laser near-field beam results in the irregular shape of the spot in the wavefront sensor. The intensity of some sub-aperture spots may be too weak to be detected, and the accuracy of wavefront restoration is seriously affected. Therefore, an extreme learning machine method is proposed to realize high precision wavefront restoration under dynamic non-uniform intensity distribution. The simulation results show that this method has better accuracy of wavefront restoration than the classical modal algorithm under dynamic non-uniform intensity distribution. The root mean square error of the residual wavefront for the proposed method is only 2.9% of the initial value.
Highlights
Atpresent, present,many manylaser laserapplications applicationsrequire requirelasers lasersto tonot notonly onlyproduce producehigh-power high-powerAt output beam, and maintain high beam quality [1,2,3,4].as the laserpower power output beam, and maintain high beam quality [1,2,3,4]
Due to the non-uniform intensity distribution of the laser beam, it is difficult for paperaccurate mainly centroid focuses on the advantages of machine learning methods on waveWFS This to detect displacements
This paper proposes the wavefront restoration technology based on the non-uniform intensity distribution
Summary
Present,many manylaser laserapplications applicationsrequire requirelasers lasersto tonot notonly onlyproduce producehigh-power high-power. Due to the non-uniform intensity distribution of the laser beam, it is difficult for paperaccurate mainly centroid focuses on the advantages of machine learning methods on waveWFS This to detect displacements. The linear regression relationship intensity of the laser presents dynamic non-uniform distribution, some sub-aperture light between Zernike mode coefficients of the wavefront and the local slopes measured by WFS spots of WFS may have an irregular shape or weak intensity. This paper measured by WFS is no longer well satisfied In this situation, it is difficult for the classical proposes the wavefront restoration technology based on the extreme learning machine modal algorithm based on Zernike polynomials to restore accurate Zernike mode (ELM) method to construct this complicated corresponding relationship under the dynamic coefficients. This paper is organized as follows: ELM method’s andthe modeling for wavefront restoration are introduced inThe
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