"The work presented in this dissertation explores the use of several unconventional imaging and wavefront sensing modalities in the presence of distributed-volume, or "deep," atmospheric turbulence. This dissertation focuses on the propagation of coherent light from laser sources through the atmosphere, and imaging/wavefront sensing at optical and infrared laser wavelengths. Such wavelengths are negatively affected by deep turbulence. We use a coherent detection method known as digital holography to (1) coherently image distant objects and (2) to sense and correct for aberrations due to turbulence along the propagation path. We showed that compensated-beacon adaptive optics can be used with a digital holographic wavefront sensor or a Shack-Hartmann wavefront sensor to improve the performance of beam projection to distant objects over uncompensated beacon adaptive optics. We saw performance gains of 17% for the Shack-Hartmann wavefront sensor and 26% for the digital holographic wavefront sensor on average for several turbulence scenarios. We explored multi-wavelength 3D imaging with digital holography along with two speckle decorrelation mechanisms that degrade 3D imaging performance in a theoretical framework. Upon establishing this framework, we simulated multi-wavelength 3D imaging of distant objects through deep turbulence and reconstructed the imagery using sharpness metric maximization for 3D data. The results showed that the reconstruction process was more successful if using more corrective phase screens along the digital propagation path. Additionally we showed that sharpness metric maximization suffered in performance in the presence of scintillated illumination patterns, also known as uplink scintillation. Finally we explored motion compensated, multi-wavelength 3D imaging with digital holography and a pilot tone in theory. Our theoretical framework predicted that one would see increased noise in range images, known as range chatter, over highly-sloped object facets relative to the optical axis, and simulations bore this out explicitly. We showed that range chatter increases as a function of object facet slope, optical illumination bandwidth, optical frequency spacing, and turbulence. Going further we used sharpness metric maximization to improve the range chatter that was brought about by turbulence."--Pages xiv-xv.

The optical quality of a coherent beam passing through a turbulent flow layer can be severely degraded by phase errors. The principle goal of this research is to model the use of wavefront sensor measurements and computed tomography to reconstruct refractive index distributions of transparent objects for the study of turbulent flows. Tomography is the processing of measurements of one-dimensional line integrals through a two-dimensional function to reconstruct a two-dimensional estimate of the function. A least-squares wavefront phase reconstructor is modeled using Zernike polynomials and triangle functions as elementary functions for the reconstructor. Two tomographic reconstruction algorithms are implemented: (1) iterative reconstruction and (2) filtered back-projection. Through numerical simulation, the effects of undersampling and limited wavefront sensor resolution are studied. Distorted wavefront data are generated by performing line integrals through known objects with different numbers and ranges of view angle. Wavefront reconstruction is applied using varying resolution. Two tomographic reconstruction methods are employed and comparisons are made with the original known objects. Results show that a least-squares wavefront reconstructor using triangle functions provides better results. Increasing the number and range of view angles generally improves the quality of the tomographic reconstruction. Furthermore, iterative tomographic reconstruction techniques prove superior when limited data are available. Optical tomography, Computed tomography, Wavefront reconstruction, Flow visualization, Three-dimensional reconstruction.

Learn how to overcome resolution limitations caused by atmospheric turbulence in Imaging Through Turbulence. This hands-on book thoroughly discusses the nature of turbulence effects on optical imaging systems, techniques used to overcome these effects, performance analysis methods, and representative examples of performance. Neatly pulling together widely scattered material, it covers Fourier and statistical optics, turbulence effects on imaging systems, simulation of turbulence effects and correction techniques, speckle imaging, adaptive optics, and hybrid imaging. Imaging Through Turbulence is written in tutorial style, logically guiding you through these essential topics. It helps you bring down to earth the complexities of coping with turbulence.

Principles of Adaptive Optics describes the foundations, principles, and applications of adaptive optics (AO) and its enabling technologies. This leading textbook addresses the fundamentals of AO at the core of astronomy, high-energy lasers, biomedical imaging, and optical communications. Key Features: Numerous examples to explain and support the underlying principles Hundreds of new references to support the topics that are addressed End-of-chapter questions and exercises A complete system design example threaded through each chapter as new material is introduced

On June 1, 2005 AFOSR awarded a grant to Michigan Technological University to investigate image reconstruction, wave front sensing, and adaptive optics in extreme imaging conditions. This is the final report for this program. The overall goal was to understand imaging under conditions where seeing is exceedingly poor, such as for space surveillance of objects at very low elevation angles, and during daytime hours. In these situations, scintillation and small isoplanatic angles dominate the image measurement and reconstruction problems. Our work was focused on performing trade-offs in the adaptive optics control algorithms for imaging under conditions of poor seeing arising from large zenith angles. In particular, we have developed a closed loop simulation of an adaptive optics system which is physically similar to the AEOS system, that uses the conventional least squares reconstructor, the exponential reconstruction, and the so-called "slope discrepancy" reconstructor. We have also examined the use of the stochastic parallel gradient descent (SPGD) algorithm for deformable mirror control in problems dominated by scintillation and anisoplanatism, and conducted a laboratory experiment to demonstrate this idea. In this report we document the results. Our work with maximum likelihood-based image reconstruction algorithms has been applied to the results provided by the adaptive optics simulation, and representative results are included here.