Abstract
This paper introduces an extended factorized geometrical autofocus (FGA) algorithm for circular synthetic aperture radar (CSAR) which is based on the FGA in stripmap synthetic aperture radar (SAR). The strategy is that integrate the FGA with a fast factorized back-projection (FFBP) processing chain and relies on varying track parameters step by step to obtain the sharp image. The focused quality of the obtained image is evaluated by computing an object function (intensity correlation). The algorithm has been tried out on a wavelength-resolution CSAR data set with erroneous track parameters. To set up constrained problems, only one track parameter is corrupted. The FGA imaging results are compared with the reference imaging results, demonstrating its excellent capacity of compensating platform trajectory movement deviation.
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