Robust Image-Based Wavefront Sensing

Several planned future optical systems, such as the James Webb Space Telescope (JWST), rely on image-based wavefront sensing for alignment, testing, and control of optical surfaces during operation. The focus of this work is on characterizing the effects of various non-idealities on the performance of image-based wavefront sensing algorithms, developing techniques to mitigate those effects, and demonstrating these techniques in computer simulations and in the lab. Two new techniques for algorithmically determining the proper sampling factor for optical propagation are presented and tested against experimental data collected in the lab and during JWST ground-based testing. A new method for mitigating against the effects of vibration on phase retrieval is discussed, implemented, and tested in simulation. The use of an alternative type of diversity, called transverse translation, is explored for use in the JWST and shown to be a promising technique through simulation. A method for extending the capture range of phase retrieval algorithms is presented and tested both in simulation and with experimental data collected in the lab. A benchmark of a phase retrieval algorithm running on a graphics card is presented and the practical implications for JWST testing are discussed. Finally, phase retrieval results from a MEMS deformable mirror testbed are presented and compared against interferometry.