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This article describes how to form a SAR image without proper motion quantities. That is within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a fast-factorized back-projection formulation with adjustable geometry parameters. Subapertures are tuned and merged pair-by-pair (base-2) and step-by-step. With this technique, we can correct an erroneous geometry and form a focused image. The FGA algorithm has been applied on two datasets, acquired by the UWB CARABAS 3 system at UHF-band. The tracks are measured accurately by means of a DGPS. We however adopt and modify a geometry model. Equidistant linear tracks at fixed altitudes are assumed. These tracks are then regulated via a two-stage search strategy and a reverseprocessing procedure. As this is a first experiment at UHF-band, we provide GPS-based length values for the subapertures, to simplify the search. Multiple geometry solutions are tested for each subaperture pair, i.e., at each resolution level. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a focused image with wavelength resolution at UHF-band, i.e., with minimum support from a motion measurement system. [ABSTRACT FROM AUTHOR]

This paper leads a discussion on how to form a Synthetic Aperture Radar (SAR) image without knowing the relative track. That is, within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection (FFBP) formulation with six free geometry parameters (per subaperture pair). These are tuned step by step until a sharp image is obtained. This innovative autofocus concept can compensate completely for an erroneous geometry. The FGA algorithm has been applied successfully on two ultrawideband (UWB) data sets, acquired by the CARABAS II system at very high frequency (VHF)-band. The relative tracks are known (measured accurately). We, however, adopt and modify a basic geometry model. A linear equidistant track at fixed altitude is initially assumed. Apart from deviations due to linearization, a ~2.5-m/s along-track velocity error is also introduced. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a wavelength-resolution SAR image at VHF-band without support from a motion measurement system. The execution time for the examples in this paper is about five times longer with autofocus than without. Hence, the FGA algorithm is now fit for use on a regular basis. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

This paper describes a factorized geometrical autofocus (FGA) algorithm, specifically suitable for ultrawideband synthetic aperture radar. The strategy is integrated in a fast factorized back-projection chain and relies on varying track parameters step by step to obtain a sharp image; focus measures are provided by an object function (intensity correlation). The FGA algorithm has been successfully applied on synthetic and real (Coherent All RAdio BAnd System II) data sets, i.e., with false track parameters introduced prior to processing, to set up constrained problems involving one geometrical quantity. Resolution (3 dB in azimuth and slant range) and peak-to-sidelobe ratio measurements in FGA images are comparable with reference results (within a few percent and tenths of a decibel), demonstrating the capacity to compensate for residual space variant range cell migration. The FGA algorithm is finally also benchmarked (visually) against the phase gradient algorithm to emphasize the advantage of a geometrical autofocus approach. [ABSTRACT FROM PUBLISHER]