Predictive adaptive optics optimal control for LEO communications in low elevation and strong scintillation conditions

Free space optical communication (FSOC) links have significant advantages over conventional radio frequency transmissions. However, optical light travelling through atmospheric turbulence is subject to varying diffraction rates that distort the wavefront phase, impacting the performance of optical links. Adaptive optics (AO) systems have been shown to mitigate these effects. An integral action controller is typically used in FSOC AO systems. The performance of these controllers is limited by the time delay. In addition, the intensity fluctuations due to scintillation can render the AO loop unstable. As a result, integrators do not perform well in strong turbulence conditions. Predictive control algorithms have the potential to improve coupling efficiency. This simulation-based study concentrates on demonstrating and quantifying the effectiveness of zonal-based linear quadratic Gaussian (LQG) regulators for LEO downlinks at low elevation and high scintillation scenarios, based on the works in Prengère et al. [J. Opt. Soc. Am. A37, 1083 (2020)10.1364/JOSAA.391484] related to satellite tracking. The simulation includes Fresnel propagation, an aspect typically neglected in existing studies. A phase oversampling and edge compensation model changes are considered as potential LQG improvements. Results are compared to a tuned integrator, and it is shown that the best performing zonal-based LQG improves mean coupling efficiency by 70%.

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Publication Details

Journal
Optics Express
Published
2025-11-11
DOI
https://doi.org/10.1364/oe.574467
Primary Topic
Optical Wireless Communication Technologies
Type
article
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article

Predictive adaptive optics optimal control for LEO communications in low elevation and strong scintillation conditions

Andrew Reeves, Gianpaolo Torre, Ilija R. Hristovski, Caroline Kulcsár et al.
Optics Express
Optical Wireless Communication Technologies
article

Predictive adaptive optics optimal control for LEO communications in low elevation and strong scintillation conditions

Andrew Reeves, Gianpaolo Torre, Ilija R. Hristovski, Caroline Kulcsár, Douglas J. Laidlaw, Joana S. Torres, Henri‐François Raynaud
article en

Abstract

Free space optical communication (FSOC) links have significant advantages over conventional radio frequency transmissions. However, optical light travelling through atmospheric turbulence is subject to varying diffraction rates that distort the wavefront phase, impacting the performance of optical links. Adaptive optics (AO) systems have been shown to mitigate these effects. An integral action controller is typically used in FSOC AO systems. The performance of these controllers is limited by the time delay. In addition, the intensity fluctuations due to scintillation can render the AO loop unstable. As a result, integrators do not perform well in strong turbulence conditions. Predictive control algorithms have the potential to improve coupling efficiency. This simulation-based study concentrates on demonstrating and quantifying the effectiveness of zonal-based linear quadratic Gaussian (LQG) regulators for LEO downlinks at low elevation and high scintillation scenarios, based on the works in Prengère et al. [J. Opt. Soc. Am. A37, 1083 (2020)10.1364/JOSAA.391484] related to satellite tracking. The simulation includes Fresnel propagation, an aspect typically neglected in existing studies. A phase oversampling and edge compensation model changes are considered as potential LQG improvements. Results are compared to a tuned integrator, and it is shown that the best performing zonal-based LQG improves mean coupling efficiency by 70%.

Optics ExpressVol. 33(24)
Durham University (GB), Institut d’Optique Graduate School (FR)
Openalex Percentile: Top 63%
Optical Wireless Communication Technologies
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Predictive adaptive optics optimal control for LEO communications in low elevation and strong scintillation conditions — Andrew Reeves, Gianpaolo Torre, et al. · Optics Express (2025) | TGRS Research Map | TGRS