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    Area of Science:

    • Atmospheric science
    • Optical remote sensing

    Background:

    • Atmospheric turbulence profiles are critical for adaptive optics, astronomical observations, and optical communications.
    • The two-aperture differential scintillation method offers a novel approach for remote sensing of turbulence.
    • Modeling turbulence profiles involves solving Fredholm integral equations, which are often ill-posed.

    Purpose of the Study:

    • To develop an accurate and robust method for retrieving atmospheric turbulence profiles.
    • To address the challenges of ill-posed integration problems in remote sensing of turbulence.
    • To improve upon existing regularized methods for atmospheric turbulence analysis.

    Main Methods:

    • Analysis of the discrete forward observation equation to define optimal integration and measurement intervals.
    • Development of an autocorrected preconditioning conjugate gradient normal residual (PCGNR) algorithm.
    • Incorporation of incremental differences, adaptive thresholds, and weighted averages for error correction within the PCGNR algorithm.

    Main Results:

    • The proposed autocorrected PCGNR algorithm effectively retrieves atmospheric turbulence profiles.
    • The method demonstrates enhanced accuracy and robustness, particularly in noisy conditions.
    • Comparison with other regularized methods shows superior performance of the developed algorithm.

    Conclusions:

    • The autocorrected PCGNR method provides a significant advancement in atmospheric turbulence profiling.
    • This technique is suitable for various remote sensing applications requiring precise turbulence data.
    • The developed algorithm offers a more reliable solution for analyzing differential scintillation data.