Backprojection Subimage Autofocus of Moving Ships for Synthetic Aperture Radar

Abstract

We propose a new autofocus approach for the backprojection reconstruction algorithm to compute high-quality synthetic aperture radar images of non-linearly moving and maneuvering ships. In contrast to the state-of-the-art autofocus techniques, our approach allows a long coherent processing interval even in the case of a rough sea, which improves the image quality. An improved image quality enables the classification of ships in airborne synthetic aperture radar (SAR) images. For this purpose, we decompose the image into subimages and estimate pulse-by-pulse a phase error for each subimage by maximizing subimage sharpness. A regularized Levenberg–Marquardt algorithm guarantees a smooth phase correction on subimage level. By correcting the subsequent range distances from the flight path to all pixels using the currently estimated phase errors, sharp images of maneuvering ships with arbitrary velocities can now be reconstructed. The evaluation of our proposed ship autofocus technique on the basis of real airborne X-band data shows that our approach leads to a visible improvement of image quality in comparison with the state-of-the-art techniques. Given these results, even an automatic ship classification based on radar images might be possible in the future.