Propagation of a radially polarized Hermite-cos-Gaussian correlated Schell-model beam in oceanic turbulence

Zhu, Pengcheng; Wang, Guiqiu; Yan, Yaotian; Yin, Yong; Zhong, Haiyang; Liu, Dajun; Wang, Yaochuan

doi:10.1016/j.ijleo.2022.170487

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…Yuan studied the evolution properties of the M 2 factor of the Hermite-Gaussian beam in turbulent atmosphere [16]. Zhu derived the propagation formula of the radially polarized Hermite-cos-Gaussian correlated Schell-model beam in oceanic turbulence [17]. Li established the model of the received probability density of orbital angular momentum (OAM) modes of a new Hermite-Gaussian vortex beam propagating through the turbulent ocean of anisotropy [16].…”

Section: Introductionmentioning

confidence: 99%

Propagation Characteristics of Rectangular Hermite-Gaussian Array Beams Through Oceanic and Atmospheric Turbulence

Du,

Ding,

et al. 2023

IEEE Photonics J.

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This study investigates the propagation characteristics of rectangular Hermite-Gaussian array beams (RHGABs) through the oceanic and atmospheric turbulence considering ocean waves. Firstly, a theoretical model for the RHGABs in seawater-to-air propagation path is proposed. Secondly, we derive the expressions of the mean squared beam width and angular spread of RHGABs by using the extended Huygens-Fresnel principle and Rytov approximation. Finally, the effects of turbulent mediums on the RHGABs spreading are studied by analyzing the Rayleigh range. Our findings suggest that the Rayleigh range increases with the beam order of RHGABs. And the mean squared beam width of RHGABs in oceanic turbulence increases significantly higher than that in atmospheric turbulence. The results of this research can be applied to underwater optical communication systems.

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Section: Introductionmentioning

confidence: 99%

Propagation Characteristics of Rectangular Hermite-Gaussian Array Beams Through Oceanic and Atmospheric Turbulence

Du,

Ding,

et al. 2023

IEEE Photonics J.

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Propagation Properties of Cosine-Gaussian-Correlated Beams in Oceanic Turbulence

李

2023

APP

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Reconstruction of degraded image transmitting through ocean turbulence via deep learning

Chen,

Liu,

Jiang

et al. 2023

J. Opt. Soc. Am. A

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When a laser carrying image information is transmitted in seawater, the presence of ocean turbulence leads to significant degradation of the received information due to the effect of interference. To address this issue, we propose a deep-learning-based method to retrieve the original information from a degraded pattern. To simulate the propagation of laser beams in ocean turbulence, a model of an ocean turbulence phase screen based on the power spectrum inversion method is used. The degraded images with different turbulence conditions are produced based on the model. A Pix2Pix network architecture is built to acquire the original image information. The results indicate that the network can realize high-fidelity image recovery under various turbulence conditions based on the degraded patterns. However, as turbulence strength and transmission distance increase, the reconstruction accuracy of the Pix2Pix network decreases. To further improve the image reconstruction ability of neural network architectures, we established three networks (U-Net, Pix2Pix, and Deep-Pix2Pix) and compared their performance in retrieving the degraded patterns. Overall, the Pix2Pix network showed the best performance for image reconstruction.

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Propagation of a radially polarized Hermite-cos-Gaussian correlated Schell-model beam in oceanic turbulence

Cited by 3 publications

References 30 publications

Propagation Characteristics of Rectangular Hermite-Gaussian Array Beams Through Oceanic and Atmospheric Turbulence

Propagation Characteristics of Rectangular Hermite-Gaussian Array Beams Through Oceanic and Atmospheric Turbulence

Propagation Properties of Cosine-Gaussian-Correlated Beams in Oceanic Turbulence

Reconstruction of degraded image transmitting through ocean turbulence via deep learning

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