Undersampled focal plane detection of imagery from a sparse telescope array.
AuthorFox, Marsha Jane.
Committee ChairShannon, Robert R.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractFor sparsely distributed arrays of optical telescopes operating in phase, large regions of complete attenuation in the modulation transfer function (MTF) result from the spaces between telescopes. These 'holes' in the MTF can be used to advantage to avoid aliasing of high spatial frequency components when the resultant optical image is undersampled by a detector array. The technique for isolating and removing the harmonic components of the sampled image spectrum from the undersampled image has been labeled 'dealiasing'. The result of undersampling the image plane is a reduction in the number of detectors required to image a particular scene by nearly a factor of four. The appropriate conditions for recovering a non-aliased image from the undersampled image focal plane are set by two parameters; the configuration of the pupil, and the detector array sampling rate. The two parameters are coupled, so that the selection of one constrains the allowed values of the other. Errors may be introduced by incorrectly scaling the pupil function to the detector array. Increasing the size of the individual subapertures in the telescope array beyond a prescribed limit also introduces errors that significantly degrade the dealiased result. The latter error is partially mitigated by the associated increase in object information transferred into the image. In this study, an algorithm is formulated to implement the dealiasing technique. The algorithm is demonstrated on point and extended objects using both an image simulation environment and a laboratory breadboard. The robustness of the algorithm to sources of error and the introduction of noise are measured. Quantitative metrics and visual assessment of image quality are used to evaluate the results. The CLEAN algorithm, a method to interpolate between the peaks of the image spectrum of the sparse telescope array is implemented. This enhancement to image quality is useful when demonstrating the concept on detailed, high resolution objects. Finally, a concept for enhancing the image quality of a sparse telescope array is presented. The technique combines imagery of two wavelengths, co-focal on the detector array. One image is of high resolution, undersampled, and dealiased. The second image is Nyquist-sampled but of low resolution. This technique significantly improves on the quality of sparse array imagery obtained at a single wavelength.
Degree ProgramOptical Sciences