An Efficient Solution to the Factorized Geometrical Autofocus Problem
Journal article, 2016

This paper describes a new search strategy within the scope of factorized geometrical autofocus (FGA) and synthetic-aperture-radar processing. The FGA algorithm is a fast factorized back-projection formulation with six adjustable geometry parameters. By tuning the flight track step by step and maximizing focus quality by means of an object function, a sharp image is formed. We propose an efficient two-stage approach for the geometrical variation. The first stage is a low-order (few parameters) parallel search procedure involving small image areas. The second stage then combines the local hypotheses into one global autofocus solution, without the use of images. This method has been applied successfully on ultrawideband CARABAS II data. Errors due to a constant acceleration are superposed on the measured track prior to processing, giving a 6-D autofocus problem. Image results, including resolution, peak-to-sidelobe ratio and magnitude values for point-like targets, finally confirm the validity of the strategy. The results also verify the prediction that there are several satisfying autofocus solutions for the same radar data.

Synthetic aperture radar (SAR)




Jan Torgrimsson

Chalmers, Earth and Space Sciences, Radar Remote Sensing

Patrik Dammert


Hans Hellsten


Lars Ulander

Swedish Defence Research Agency (FOI)

Chalmers, Earth and Space Sciences, Radar Remote Sensing

IEEE Transactions on Geoscience and Remote Sensing

0196-2892 (ISSN)

Vol. 54 8 4732-4748

Areas of Advance

Information and Communication Technology

Subject Categories

Signal Processing



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