Autocorrected preconditioning regularization inversion algorithm for an atmospheric turbulence profile

摘要

Atmospheric turbulence profiles have great significance for adaptive optics, astronomical observations, laser propagation in atmospheres, and free space optical communications. The two-aperture differential scintillation method is a recent approach for analyzing remote-sensing atmospheric turbulence profiles that utilizes active beacons to make it suitable for different measurement situations. The relationship between differential scintillation and atmospheric turbulence profiles can be modeled using the Fred holm integral equation. To address this ill-posed integration problem, the discrete forward observation equation is first analyzed to obtain better integration intervals and measurement intervals needed for inversion. Then an autocorrected preconditioning conjugate gradient normal residual (PCGNR) algorithm is proposed to acquire atmospheric turbulence profiles. The algorithm contains a developed autocorrection strategy that incorporates incremental differences, adaptive thresholds, and weighted averages to correct for artefacts and marginal errors that arise from the PCGNR method. Compared with other regularized methods, the proposed autocorrected PCGNR method is more accurate and robust in the presence of noise. (C) 2020 Optical Society of America