Adaptive merit function in SPGD algorithm for beam combining

The beam pointing is the most crucial issue for beam combining to achieve high energy laser output. In order to meet the turbulence situation, a beam pointing method that cooperates with the stochastic parallel gradient descent（SPGD） algorithm is proposed. The power-in-the-bucket（PIB） is chosen as t...

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Bibliographic Details
Published in:Optoelectronics letters 2016-09, Vol.12 (5), p.398-400
Main Author: 杨国庆 刘立生 姜振华 王挺峰 郭劲
Format: Article
Language:English
Subjects:
Adaptive algorithms
Computer simulation
D算法
Laser beams
Lasers
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
SPG
Turbulence
价值函数
梯度下降
波束指向
激光输出
自适应
评价函数
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Summary:The beam pointing is the most crucial issue for beam combining to achieve high energy laser output. In order to meet the turbulence situation, a beam pointing method that cooperates with the stochastic parallel gradient descent（SPGD） algorithm is proposed. The power-in-the-bucket（PIB） is chosen as the merit function, and its radius changes gradually during the correction process. The linear radius and the exponential radius are simulated. The results show that the exponential radius has great promise for beam pointing.
ISSN:1673-1905
1993-5013
DOI:10.1007/s11801-016-6150-y