Parameters Optimization of the Beam Cleanup System Based on Stochastic Parallel Gradient Descent Method

被引：0
|
作者：
Wang Sanhong [1 ,2 ]
Cui Junfeng [2 ]
Ma Haotong [3 ]
Liang Yonghui [3 ]
Yu Qifeng [1 ]
机构：
[1] Natl Univ Def Technol, Coll Aerosp & Mat Engn, Changsha 410073, Hunan, Peoples R China
[2] Taiyuan Satellite Launch Ctr, Taiyuan 030027, Shanxi, Peoples R China
[3] Natl Univ Def Technol, College Opto Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China
来源：
HIGH-POWER LASERS AND APPLICATIONS VI | 2012年 / 8551卷
基金：
中国国家自然科学基金;
关键词：
high-energy laser; beam cleanup; adaptive optics; stochastic parallel gradient descent; parameters optimization; ADAPTIVE OPTICS SYSTEM; COMPENSATION;
D O I：
10.1117/12.982001
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In a high-energy laser, the thermal aberrations degrade the beam quality and reduce the laser's output power. Adaptive optics (AO) technique based on a stochastic parallel gradient (SPGD) algorithm can be used to compensate for the distortions in real time to clean up the laser beam. Such a beam clean-up system was simulated and experiments were conducted to study the optimization of the parameters of the gain coefficient and the amplitude of the perturbation. The results show that the convergence property of the SPGD algorithm is improved after the parameters being optimized.
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页数：7
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