Synthetic Aperture Radar Image Processing on Parallel Supercomputers
S. J. Plimpton, G. A. Mastin, D. Ghiglia, in Proc of Supercomputing '91, Albuquerque, NM, November 1991, p 446.
We briefly discuss three algorithms used to process synthetic aperture radar (SAR) images: a polar reformatter that maps raw SAR data to a rectangular mesh, 2-d FFTs that convert the data set to a real image, and phase gradient autofocusing which creates clear images by correcting blurs resulting from uncompensated phase errors. Implementation details and performance data for the algorithms are given for two parallel supercomputers, a nCUBE 2 hypercube and a CM-2. Portions of the algorithms execute at gigaflop speeds, meaning that large SAR data sets (16,384 x 65,536) can be processed in tens of minutes instead of hours as on conventional supercomputers. Equally significantly, the gigabytes of internal memory on the parallel machines allow entire images to be processed in place.
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