Demand for high-resolution imaging capabilities for both space-based and ground-based imaging systems has created significant interest in improving the design of multi-aperture interferometry imaging systems. Interferometers are a desirable alternative to single aperture imaging systems due to the fact that the angular resolution of a single aperture system is dependent on the diameter of the aperture and the resolution of the image recording device (CCD or otherwise) which quickly results in increased size, weight, and cost. Interferometers can achieve higher angular resolutions with lower resolution recording mediums and smaller apertures by increasing the distance between the apertures. While these systems grow in both size, mechanical, and computational complexity, methods of testing large scale designs with small scale demonstration systems currently do not exist. This paper documents the performance of a small scale multi-aperture intensity correlation interferometer which is used to view a double slit image. The interferometer consists of 2 avalanche photo-diodes connected to a data acquisition computer. The image is produced by shining light through the double slit image an image containment system. The sensors are placed at the far end of the image containment system, and their voltages are recorded and digitally filtered. This study presents the formulation of the design parameters for the interferometer, the assembly and design of the interferometer, and then analyzes the results of the imaging experiment and the methods used to attempt to prevent unwanted noise from corrupting the expected interference pattern. Codes in C and C++ are used to collect and analyze the data, respectively, while Matlab® was used to produce plots of binary data. The results of the analysis are then used to show that a small scale intensity correlation interferometer is indeed feasible and has promising performance.

As astronomers and astrophysicists seek to view ever-increasingly distant celestial objects, the desired angular resolution of telescopes is constantly being increased. Classical optics, however, has shown a proportional relationship between the size of an optical telescope and the possible angular resolution. Experience has also shown that prohibitive cost accompanies large optical systems. With these limitations on classical optical systems and with the drastic increase in computational power over the past decade, intensity correlation interferometry (ICI) has seen renewed interest since the 1950’s and 60’s when it was initially conceived by Hanbury Brown and Twiss. Intensity correlation interferometry has the advantage of less stringent equipment precision and less equipment cost when compared to most other forms of interferometry. ICI is thus attractive as a solution to the desire for high angular resolution imaging especially in space based imaging systems. Optical interferometry works by gathering information about the Fourier transform of the geometry of an optical source. An ICI system, however, can only detect the magnitude of the Fourier components. The phase of the Fourier components must be recovered through some computational means and typically some a priori knowledge of the optical source. This thesis gives the physics and mathematical basis of the intensity correlation interferometer. Since the ICI system cannot detect the phase of an optical source's Fourier transform, some known methods for recovering the phase information are discussed. The primary method of interest here is the error-reduction algorithm by Gerchberg-Saxton which was adapted by Fienup to phase retrieval. This algorithm works by using known qualities of the image as constraints; however, sometimes it can be difficult to know what these constraints are supposed to be. A method of adaptively discovering these constraints is presented, and its performance is evaluated in the presence of noise. Additionally, an algorithm is presented to adapt to the presence of noise in the Fourier modulus data. Finally, the effects of the initial condition of the error-reduction algorithm are shown and a method of mitigating its effect by averaging several independent solutions together is shown.

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