Application of hybrid modal algorithm in wavefront sensorless adaptive optics

Liu Wujie; Yuan Xiuhua; Zhou Zeyu; Li Qi; Zhao Ming

doi:10.12086/oee.2022.220020

Article navigation > Opto-Electronic Engineering > 2022 Vol. 49 > No. 12 > 220020

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Liu W J, Yuan X H, Zhou Z Y, et al. Application of hybrid modal algorithm in wavefront sensorless adaptive optics[J]. Opto-Electron Eng, 2022, 49(12): 220020. doi: 10.12086/oee.2022.220020

Citation:

Liu W J, Yuan X H, Zhou Z Y, et al. Application of hybrid modal algorithm in wavefront sensorless adaptive optics[J]. Opto-Electron Eng, 2022, 49(12): 220020. doi: 10.12086/oee.2022.220020

Application of hybrid modal algorithm in wavefront sensorless adaptive optics

School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

Fund Project: National Natural Science Foundation of China (62005088)

More Information

^*Corresponding author: yuanxh@hust.edu.cn

Received Date 18 March 2022

Revised Date 05 August 2022

Accepted Date 06 September 2022

Available Online 29 November 2022

Published Date 25 December 2022

Abstract

Abstract

The Lukosz pre-correction modal algorithm can correct low-order aberrations of wavefront distortion and narrow the search range of iterative algorithms. The adaptive cosine-decay stochastic parallel gradient descent (AcSPGD) algorithm can compensate for high-order aberrations of wavefront distortion and improve the correction accuracy of iterative algorithms. In this paper, a new hybrid modal algorithm based on the pre-correction model and AcSPGD algorithm is applied to correct wavefront distortion in wavefront sensorless adaptive optics, and the feasibility of the optimization algorithm is also verified by the experiments. Experimental results show that the correction speed of the hybrid modal algorithm is two times faster than the commonly used stochastic parallel gradient descent (SPGD) algorithm, and the correction accuracy of the hybrid modal algorithm is better than the traditional Lukosz modal algorithm. Applied to wavefront sensorless adaptive optics, the optimization algorithm effectively reduces the phase fluctuation of the wavefront and improves the far-field Strehl ratio (SR), thus improving the communication performance of the free-space optical communication (FSO) system.
- free-space optical communications /
- wavefront sensorless adaptive optics /
- stochastic parallel gradient descent algorithm /
- Lukosz model

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References

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Overview

Overview

With the advent of the 5G era, the general demand for big data processing makes the stable transmission of high-speed and high-capacity links more and more important. However, when the laser is transmitted in the atmosphere, natural phenomena such as air flow, temperature change, rain, fog, and snow will seriously undermine the stability and reliability of atmospheric link transmission. Among all proposed methods of compensating for atmospheric turbulence effects, the wavefront sensorless adaptive optics becomes the most effective technology to correct wavefront distortion caused by atmospheric turbulence, which can improve communication performances when applied in atmospheric laser communications. The final correction results of wavefront sensorless adaptive optics are often determined by different optimization algorithms which can be divided into model-free optimization algorithms and model-based optimization algorithms. However, both types of algorithms have certain limitations. The iterations of the model-free algorithms are so numerous that the convergence rate is very slow. The model-based algorithms have great correction speed, but can only correct low-order aberrations of wavefront distortion, so they are too easy to fall into local convergence and their correction accuracy is very low. Therefore, a critical technical problem of free-space optical communications is how to improve the convergence rate and correction accuracy of the iterative algorithms at the same time.

The Lukosz pre-correction modal algorithm can correct low-order aberrations of wavefront distortion and narrow the search range of iterative algorithms. The adaptive cosine-decay stochastic parallel gradient descent (AcSPGD) algorithm can compensate for high-order aberrations of wavefront distortion and improve the correction accuracy of iterative algorithms. In this paper, a new hybrid modal algorithm based on the pre-correction model and AcSPGD algorithm is applied to correct wavefront distortion in wavefront sensorless adaptive optics, and the feasibility of the optimization algorithm is also verified by the experiments. Experimental results show that the correction speed of the hybrid modal algorithm is two times faster than the commonly used stochastic parallel gradient descent (SPGD) algorithm, and the correction accuracy of the hybrid modal algorithm is better than the traditional Lukosz modal algorithm. Applied to wavefront sensorless adaptive optics, the optimization algorithm effectively reduces the phase fluctuation of the wavefront and improves the far-field Strehl ratio, which thus improves the signal-to-noise ratio of the atmospheric laser communication system by 2.9 dB, reduces the bit error rate to 10⁻⁶, and improves the communication performance of the free-space optical communication system. The hybrid modal algorithm has great reference and application value.