A Novel SAR Sidelobe Suppression Method via Dual-Delta Factorization

A novel synthetic aperture radar (SAR) sidelobe suppression method via a dual-Delta factorization (DDF) algorithm is proposed in this letter. Its basic idea is to divide the point spread function (PSF) into a group of different simple subsystems (dual-Delta operators) and to asymptotically approach the solution by the subsystem iterations based on the greedy strategy. The convergence of the DDF algorithm is discussed based on theoretical analyses and numerical experiments. We find that, to keep the algorithm convergent, the sidelobe sum should be soundly smaller than that of the main lobe during the iterations. Simulation experiments and actual SAR image results show that the DDF algorithm can deal with all kinds of PSFs without their exact expressions and is compatible with nonseparable cases, which makes it suitable to process the squint SAR and bistatic SAR images.