Acta Optica Sinica, Volume. 42, Issue 6, 0626001(2022)

Feedback Wavefront Manipulation Method Based on Genetic Gradient Particle Swarm Optimization Algorithm Under Strong Noise

Pingjiang Ling1, Yanrui Zhang1, Boyu Tian1, Keyu Li2, Nianchun Sun1, and Bin Zhang1、*
Author Affiliations
  • 1School of Electronics and Information Engineering, Sichuan University, Chengdu, Sichuan 610064, China
  • 2Research Center of Laser Fusion, China Academy of Engineering Physics, Mianyang, Sichuan 621900, China
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    When a laser beam passes through a transparent scattering medium, a speckle field is usually generated. The phase of the incident beam can be adjusted proactively by using feedback wavefront control technique, and the speckle can be formed into focused speckle. When there is strong noise interference, most of the existing feedback control algorithms have the problem of unsatisfactory regulation effect. Therefore, a feedback wavefront regulation method based on genetic gradient particle swarm optimization algorithm is proposed for strong noise environment. This method does not rely too much on the previous optimization information, but combines the function of gradient rapid search and gene cross mutation to realize the laser beam regulation in noisy environment. The effects of initial parameters (adjustment factor, mutation rate, crossover rate, etc.) and search ability of gradient particle swarm optimization on regulation effect are analyzed by comparing with traditional algorithm. The results show that under the strong background stray light noise in the bright room, the genetic gradient particle swarm optimization algorithm can achieve better focusing effect in less iterations.

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    Pingjiang Ling, Yanrui Zhang, Boyu Tian, Keyu Li, Nianchun Sun, Bin Zhang. Feedback Wavefront Manipulation Method Based on Genetic Gradient Particle Swarm Optimization Algorithm Under Strong Noise[J]. Acta Optica Sinica, 2022, 42(6): 0626001

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    Paper Information

    Category: Physical Optics

    Received: Jul. 20, 2021

    Accepted: Sep. 28, 2021

    Published Online: Mar. 8, 2022

    The Author Email: Zhang Bin (zhangbinff@sohu.com)

    DOI:10.3788/AOS202242.0626001

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