TY - JOUR
T1 - 采用深度学习校正畸变涡旋光束的方法综述(特邀)
AU - Wang, Jiaqi
AU - Fu, Shiyao
AU - Li, Lang
AU - Guo, Yingchi
AU - Li, Chen
AU - Gao, Chunqing
N1 - Publisher Copyright:
© 2022 Chinese Society of Astronautics. All rights reserved.
PY - 2022/7
Y1 - 2022/7
N2 - Vortex beam is a kind of novel structured beam with helical wavefront and carries orbital angular momentum (OAM). Such structured field can find applications in many domains as large-capacity data transmission, remote detection, etc. The wavefront aberration occurs when the vortex beam propagates in a non-homogeneous medium as atmosphere turbulence, resulting in the OAM changing and go against practical applications. Therefore, it is necessary to compensate distorted vortex beams through adaptive optics. The recent advances on adaptive correction of distorted vortex beams was mainly reviewed. The current mature correction schemes were firstly introduced in brief, including wavefront sensing along with probe Gaussian beams, array detection along with phase retrieval algorithms, and so on. Then the deep-learning-based approaches were highlighted, as Zernike polynomial coefficients inversion, turbulence phase screen inversion, etc. The advantages and limitations of employing deep learning for distorted vortex beam compensation were also discussed. Finally, development trends of distortion compensation of vortex beams were prospected.
AB - Vortex beam is a kind of novel structured beam with helical wavefront and carries orbital angular momentum (OAM). Such structured field can find applications in many domains as large-capacity data transmission, remote detection, etc. The wavefront aberration occurs when the vortex beam propagates in a non-homogeneous medium as atmosphere turbulence, resulting in the OAM changing and go against practical applications. Therefore, it is necessary to compensate distorted vortex beams through adaptive optics. The recent advances on adaptive correction of distorted vortex beams was mainly reviewed. The current mature correction schemes were firstly introduced in brief, including wavefront sensing along with probe Gaussian beams, array detection along with phase retrieval algorithms, and so on. Then the deep-learning-based approaches were highlighted, as Zernike polynomial coefficients inversion, turbulence phase screen inversion, etc. The advantages and limitations of employing deep learning for distorted vortex beam compensation were also discussed. Finally, development trends of distortion compensation of vortex beams were prospected.
KW - adaptive optics
KW - atmospheric turbulence
KW - deep learning
KW - vortex beam
KW - wavefront correction
UR - http://www.scopus.com/inward/record.url?scp=85137617208&partnerID=8YFLogxK
U2 - 10.3788/IRLA20220221
DO - 10.3788/IRLA20220221
M3 - 文章
AN - SCOPUS:85137617208
SN - 1007-2276
VL - 51
JO - Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
JF - Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
IS - 7
M1 - 20220221
ER -