Dynamic DH-MBIR for low-latency wavefront estimation in the presence of atmospheric boiling

Ali G. Sheikh; Casey J. Pellizzari; Sherman J. Kisner; Gregery T. Buzzard; Charles A. Bouman

doi:10.1117/12.2676406

3 October 2023 Dynamic DH-MBIR for low-latency wavefront estimation in the presence of atmospheric boiling

Ali G. Sheikh, Casey J. Pellizzari, Sherman J. Kisner, Gregery T. Buzzard, Charles A. Bouman

Proceedings Volume 12693, Unconventional Imaging, Sensing, and Adaptive Optics 2023; 1269308 (2023) https://doi.org/10.1117/12.2676406
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

The estimation of phase errors due to atmospheric turbulence from digital-holography (HD) data with high throughput and low latency is critical for applications such as wavefront sensing and directed energy. The problem of focusing outgoing directed energy is particularly difficult because the phase errors must be estimated with extremely low latency for use in closed-loop correction of the outgoing light before the atmospheric parameters decorrelate. This low latency requirement necessitates that the phase distortion be estimated from a single shot of DH data. The Dynamic DH-MBIR (DDH-MBIR) algorithm has been shown to be capable of accurately estimating isoplanatic phase-errors using the expectation-maximization (EM) algorithm; however, DDH-MBIR was introduced using data that models only frozen flow of atmospheric turbulence. In this paper, we characterize the performance of the Dynamic DH-MBIR algorithm in more realistic settings. Specifically, Dynamic DH-MBIR produces accurate phase estimates in the case of moderate levels of atmospheric boiling.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ali G. Sheikh, Casey J. Pellizzari, Sherman J. Kisner, Gregery T. Buzzard, and Charles A. Bouman "Dynamic DH-MBIR for low-latency wavefront estimation in the presence of atmospheric boiling", Proc. SPIE 12693, Unconventional Imaging, Sensing, and Adaptive Optics 2023, 1269308 (3 October 2023); https://doi.org/10.1117/12.2676406

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