Identification of the dynamics of time-varying phase aberrations from time histories of the point-spread function

Reinier Doelman, Måns Klingspor, Anders Hansson, Johan Löfberg, Michel Verhaegen

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Abstract

To optimally compensate for time-varying phase aberrations with adaptive optics, a model of the dynamics of the aberrations is required to predict the phase aberration at the next time step. We model the time-varying behavior of a phase aberration, expressed in Zernike modes, by assuming that the temporal dynamics of the Zernike coefficients can be described by a vector-valued autoregressive (VAR) model. We propose an iterative method based on a convex heuristic for a rank-constrained optimization problem, to jointly estimate the parameters of the VAR model and the Zernike coefficients from a time series of measurements of the point-spread function (PSF) of the optical system. By assuming the phase aberration is small, the relation between aberration and PSF measurements can be approximated by a quadratic function. As such, our method is a blind identification method for linear dynamics in a stochastic Wiener system with a quadratic nonlinearity at the output and a phase retrieval method that uses a time-evolution-model constraint and a single image at every time step.

Original languageEnglish
Pages (from-to)809-817
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume36
Issue number5
DOIs
Publication statusPublished - 2019

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