KEYWORDS: Expectation maximization algorithms, Simulations, Atmospheric turbulence, Distortion, Wavefront sensors, Directed energy weapons, Data modeling, Air force
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.
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