Scintillation resistant wavefront sensing based on multi-aperture phase reconstruction technique.

A scintillation resistant sensor that allows retrieval of an input optical wave phase using a multi-aperture phase reconstruction (MAPR) technique is introduced and analyzed. The MAPR sensor is based on a low-resolution lenslet array in the classical Shack-Hartmann arrangement and two high-resolution photo-arrays for simultaneous measurements of pupil- and focal-plane intensity distributions, which are used for retrieval of the wavefront phase in a two stage process: (a) phase reconstruction inside the sensor pupil subregions corresponding to lenslet subapertures and (b) recovery of subaperture averaged phase components (piston phases). Numerical simulations demonstrate the efficiency of the MAPR technique in conditions of strong intensity scintillations and the presence of wavefront branch points.

Imaging with an array of adaptive subapertures.

An imaging system composed of an array of adaptive optics subapertures referred to as a conformal imaging system is considered. A conformal image of an object viewed through atmospheric turbulence is obtained using the following sequential steps: adaptive compensation of phase distortions through optimization of image quality metrics at each subaperture, measurements of the phase and intensity distributions corresponding to the compensated subaperture images, digital combining and processing of the obtained data, computation of a conformal image using arbitrary phase shifts between subapertures, and correction of these phase shifts through conformal image quality optimization using the stochastic parallel gradient descent algorithm. Numerical simulation results of a dual-star conformal image through atmospheric turbulence are presented.

Approach for reconstructing anisoplanatic adaptive optics images.

Atmospheric turbulence corrupts astronomical images formed by ground-based telescopes. Adaptive optics systems allow the effects of turbulence-induced aberrations to be reduced for a narrow field of view corresponding approximately to the isoplanatic angle theta(0). For field angles larger than theta(0), the point spread function (PSF) gradually degrades as the field angle increases. We present a technique to estimate the PSF of an adaptive optics telescope as function of the field angle, and use this information in a space-varying image reconstruction technique. Simulated anisoplanatic intensity images of a star field are reconstructed by means of a block-processing method using the predicted local PSF. Two methods for image recovery are used: matrix inversion with Tikhonov regularization, and the Lucy-Richardson algorithm. Image reconstruction results obtained using the space-varying predicted PSF are compared to space invariant deconvolution results obtained using the on-axis PSF. The anisoplanatic reconstruction technique using the predicted PSF provides a significant improvement of the mean squared error between the reconstructed image and the object compared to the deconvolution performed using the on-axis PSF.