Wavefront sensing requirements for high-speed AO in deep turbulence

Harshil Dave; Edwin Ahn; Steve Gibson

doi:10.1117/12.3027000

7 October 2024 Wavefront sensing requirements for high-speed AO in deep turbulence

Harshil Dave, Edwin Ahn, Steve Gibson

Proceedings Volume 13149, Unconventional Imaging, Sensing, and Adaptive Optics 2024; 131490K (2024) https://doi.org/10.1117/12.3027000
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Abstract

Applications utilizing free space beam propagation over long distances in the atmosphere require active sensors and beam shaping. New wavefront sensor designs promise improved performance in deep turbulence, but comprehensive comparisons of modern wavefront sensor designs within Adaptive Optics (AO) loops have yet to reveal winning system-level designs for adaptive optics systems capable of correcting deep turbulence. Here, we attempt to shed light on the problem using a comprehensive wave optics model to evaluate a least-squares based and interferometric-based wavefront sensing techniques, namely the Shack-Hartmann wavefront sensor and pupil plane off-axis digital holography in combination with optimal and adaptive predictive control. The Shack Hartmann wavefront sensor has been an established wavefront sensor that provides a measurement of the wavefront through fast measurements of the wavefront gradient and least squares reconstruction. Interferometric techniques such as digital holography provide higher resolution wavefront reconstruction and improved performance with strong turbulence but with stricter laser requirements and larger computation time. For an optimal AO design in a given application, there is a trade-off between reconstructed wavefront resolution and speed. In this paper, we use wave-optics simulation to qualitatively discuss the upper bounds of AO in deep turbulence, spatial resolution limitations of Shack-Hartmann and Digital Holography wavefront sensors. We show preliminary results of closed-loop AO performance in dynamic deep turbulence, inclusive of wind and limited spatial resolution. Additionally, we show a preliminary analysis of using predictive control to improve the temporal performance of an AO loop and compensate for latencies due to hardware.

Conference Presentation

Citation Download Citation

Harshil Dave, Edwin Ahn, and Steve Gibson "Wavefront sensing requirements for high-speed AO in deep turbulence", Proc. SPIE 13149, Unconventional Imaging, Sensing, and Adaptive Optics 2024, 131490K (7 October 2024); https://doi.org/10.1117/12.3027000

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