Research Progress on Atmospheric Turbulence Perception and Correction Based on Adaptive Optics and Deep Learning
Year: 2025
Type: article
Abstract: Atmospheric turbulence constitutes a fundamental limiting factor in astronomical observation systems and laser communication architectures. During atmospheric propagation of optical beams, dynamically evolving wavefront aberrations are inevitably induced, rendering precise turbulence characterization and mitigation critical for optimizing operational performance of terrestrial telescopes and satellite‐ground optical links. Adaptive optics (AO) represents a sophisticated methodology for optical enhancement through real‐time wavefront measurement and adaptive compensation of medium‐induced phase distortions. Recent years have witnessed substantial advancements in AO technology, driven by synergistic progress in fundamental theories, optoelectronic devices, and computational algorithms. Furthermore, artificial intelligence‐driven turbulence processing frameworks leveraging deep neural networks have emerged as a prominent research frontier, demonstrating remarkable potential in intelligent wavefront sensing and nonlinear compensation. This work presents a systematic review of atmospheric turbulence fundamentals, including theoretical formulations and AO‐based mitigation strategies. Particular emphasis is placed on deep learning‐enabled intelligent correction paradigms, while critical analysis is provided regarding prospective research trajectories and implementation challenges.
Source: Advanced Photonics Research
Authors: Qinghui Liu, Yihang Di, Mengmeng Zhang, Zhenbo Ren, Jianglei Di, Jianlin Zhao
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,070
Funders: Guangdong Innovative and Entrepreneurial Research Team Program, National Natural Science Foundation of China, China Postdoctoral Science Foundation, Fundamental Research Funds for Central Universities of the Central South University, Basic and Applied Basic Research Foundation of Guangdong Province
OpenAlex ID: W4408983956