Wavefront Curvature Sensing from Image Projections

This research outlines the development and simulation of a signal processing approach to real time wavefront curvature sensing in adaptive optics. The signal processing approach combines vectorized Charge Coupled Device (CCD) read out with a wavefront modal estimation technique. The wavefront sensing algorithm analyzes vector projections of image intensity data to provide an estimate of the wavefront phase as a combination of several low order Zernike polynomial modes. This wavefront sensor design expands on an existing idea for vector based tilt sensing by providing the ability to compensate for additional modes. Under the proposed wavefront sensing approach, the physical wavefront sensor would be replaced by a pair of imaging devices capable of generating vector projections of the image data. Using image projections versus two-dimensional image data allows for faster CCD read out and decreased read noise