Wavefront curvature sensing from image projections.

摘要

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.; The primary research contribution is to create an effective method for estimating low order wavefront modes from image vector information. This dissertation provides simulation results and Cramer-Rao performance bounds for two wavefront sensor designs. The first sensor provides estimates of tilt and defocus: Zernike polynomials 2 through 4. The second sensor estimates Zernike polynomials 2 through 10. Sensors are simulated in guide star applications under the influence of von Karman atmospheric phase aberrations and CCD noise models. Secondary research contributions include identifying key algorithm performance parameters, and parameter sensitivity as well as an investigation of strategies for improving extensible phase screen generation.; A simulated performance comparison is conducted between the Z2-4 and the Z2-10 sensors, and a centroiding tilt sensor and a projection based maximum likelihood tilt sensor. Simulation trials using a subaperture diameter of 0.07m stepped through values of r0 from 0.04 to 0.14m and average photon counts of 100 to 1000. The Z2-4 sensor provides superior performance over both tilt sensors in all trials conducted. The Z2-10 sensor outperforms both tilt sensors when the average photon count is greater than 200 photons, and performance on par with both tilt sensors when the average photon count is between 100 and 200 photons.