Compensation of turbulence-induced wavefront aberration with convolutional neural networks for FSO systems

Chen, Minan; Jin, Xianqing; Li, Shangbin; Xu, Zhiwei

doi:10.3788/col202119.110601

Cited by 12 publications

(5 citation statements)

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“…The actual light exists in the form of partial coherence. Besides, the tilt aberration 24 , 25 cannot be neglected because tilt aberration will degrade the heterodyne efficiency severely, 14 so it is meaningful to analyze the effect of tilt aberration on heterodyne efficiency based on partially coherent beam. However, no researcher has carried out such work.…”

Section: Introductionmentioning

confidence: 99%

Numerical study of tilt aberration on heterodyne efficiency using partially coherent beam

Liu,

Chen

2024

Opt. Eng.

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In a coherent Doppler wind lidar detection system, heterodyne efficiency is an extremely important parameter that reflects the matching degree between local oscillator (LO) light and signal light. More generally, assuming that both the LO light and signal light are partially coherent beams based on the Gaussian-Schell model, we have derived an analytical expression for the heterodyne efficiency in the presence of tilt aberration. The expression indicates that the heterodyne efficiency not only depends on the tilt aberration but also is influenced by the beam parameters, misalignment angle, detector diameter, and wavelength. Specific examples of the variation in heterodyne efficiency with these factors are given in the simulation section. The numerical results show that if high heterodyne efficiency is required, the intensity width of the LO light does not have to be large when the intensity width of the signal light is determined; besides, setting w s ∕w LO ¼ 0.5 is appropriate, where w s and w LO are the intensity width of signal and LO, respectively. Even if LO is a partially coherent beam, the heterodyne efficiency can still reach the global maximum of 0.86, and setting δ s ∕δ LO ¼ 0.6 is suitable, where δ s and δ LO are the coherence width of the signal and LO, respectively. As expected, the bigger the δ s is, the higher the heterodyne efficiency is. For the same heterodyne efficiency, the tilt aberration can be larger slightly when the misalignment angle is small. We also find that the detector diameter plays a significant role in enhancing the heterodyne efficiency, and it is beneficial to choose a small detector diameter. Besides, the tilt aberration in the system should be less than 0.5λ. Moreover, we show that the rate of decrease in heterodyne efficiency with the tilt aberration is different for different misalignment angles. We also have demonstrated that the longer the wavelength, the higher the heterodyne efficiency for system with the same tilt aberration.

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Section: Introductionmentioning

confidence: 99%

Numerical study of tilt aberration on heterodyne efficiency using partially coherent beam

Liu,

Chen

2024

Opt. Eng.

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“…Due to the chaotic behavior of the turbulent atmosphere, stochastic processes such as temperature and pressure cannot be approximated as stationary during the measurements. Extensive studies have illustrated the significance of obtaining precise low‐layer

{C}_{n}^{2}

vertical profiles to evaluate the impact of atmospheric turbulence on the performance of photoelectric systems 2–4 . In this Letter, we propose an alternative

{C}_{n}^{2}

profile estimation approach that is both computationally inexpensive and capable of real‐time acquisition.…”

Section: Introductionmentioning

confidence: 99%

“…Extensive studies have illustrated the significance of obtaining precise low-layer C n 2 vertical profiles to evaluate the impact of atmospheric turbulence on the performance of photoelectric systems. [2][3][4] In this Letter, we propose an alternative C n 2 profile estimation approach that is both computationally inexpensive and capable of real-time acquisition.…”

Section: Introductionmentioning

confidence: 99%

A vertical DIM lidar for refractive index structure parameter profiles estimation in low‐layer atmosphere

Qiu

Wang

Hou

et al. 2023

Micro & Optical Tech Letters

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This Letter presents an experimental demonstration of a vertical differential image motion (DIM) lidar for calculating the profiles of the low-layer atmospheric refractive index structure parameters. Utilizing the differences between weighting functions, we propose a convenient approach for the realtime estimation of low-layer C n 2 profiles from DIM lidar data. This approach only requires returned fluxes as input, yet it has the intrinsic ability to capture real-time turbulence profiles. Validations against the collected observational data have shown this approach to be computationally inexpensive. The longterm comparisons with micro-thermometers indicate that in such a way vertical DIM lidars can be used for providing not only a general assessment of turbulence effects along the measurement path but turbulence profiles.

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“…In fact, the majority of these algorithms can be described as analytical applications of various estimation frameworks. But amid a large wave of general advances in Neural-network (NN), NN-based methods have been widely used for wavefront reconstruction and prediction of AO systems [17][18]. It turns out that NN-based methods have the advantage over analytical estimation techniques in terms of alleviating time delay, because NN predictors are self-optimizing, generalizable and have strong nonlinear fitting ability [18][19].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Prediction Algorithm on Atmospheric Turbulence-Induced Wavefront for Adaptive Optics

Wang

Zhu

et al. 2022

IEEE Photonics J.

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Correction performance of an adaptive optics (AO) system is severely limited by its system latency under high temporal frequency distortions. Wavefront prediction methods has been proven to be an effective way to compensate system delay. A novel wavefront prediction method based on residual learning fusion network (RLFNet) is proposed in this paper. The network is able to eliminate redundant information between adjacent wavefront frames and fuse refined features, which provides a higher prediction accuracy under fewer priori wavefront input. The method is tested on a 1km laser atmospheric transmission experimental setup through high frequency atmospheric turbulence, where wavefront data is collected from a 1kHz Shack-Hartmann wavefront sensor (SHWS). We show that the proposed architecture is able to predict the second frame wavefront after the previous 6 frames with a root-mean-square (RMS) wavefront error reduction up to 53% compare to non-predictive method.

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Compensation of turbulence-induced wavefront aberration with convolutional neural networks for FSO systems

Cited by 12 publications

References 0 publications

Numerical study of tilt aberration on heterodyne efficiency using partially coherent beam

Numerical study of tilt aberration on heterodyne efficiency using partially coherent beam

A vertical DIM lidar for refractive index structure parameter profiles estimation in low‐layer atmosphere

Deep Learning-Based Prediction Algorithm on Atmospheric Turbulence-Induced Wavefront for Adaptive Optics

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