Comparison of super-resolution techniques for SAR preprocessing

To increase the spatial resolution of synthetic aperture radar (SAR) images, we process the received data through super-resolution methods instead of conventional pulse compression. Since the problem of SAR processing is 'ill-posed', we must apply regularization techniques by incorporating prior knowledge about the imaged scene. We review restoration techniques with prior knowledge based on known deterministic properties of the solution or formulated in terms of a priori probability distributions. Moreover, we pose the scattering cross section problem as a maximum-likelihood one, and we maximize the likelihood function through optimization algorithms. Numerical results demonstrate that the classical resolution limit can be overcome by using certain super-resolution techniques.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.