Wavefront Sensing For Anisotropic Turbulence Using Digital Holography

We report on digital holographic imaging through atmospheric turbulence. Data recorded with aberrations is corrected during post processing using an iterative sharpness-metric maximization algorithm. Assuming the correction cancels the actual wavefront error, this process is equivalent to wavefront sensing. Much of our past work focused on imaging through isotropic turbulence with phase corrections using a Zernike-polynomial expansion. Here, we describe algorithm modifications for imaging through anisotropic turbulence, similar to what is seen when looking through the aero-optic boundary layer surrounding a moving aircraft. Specifically, we explore tradeoffs associated with switching from a Zernike representation to Karhunen-Loeve basis functions. In some cases, the dimensionality of the phase correction estimation algorithm can be reduced significantly by this change. This reduces the computational burden