A review of super-resolution inverse synthetic aperture radar imaging algorithms

Abstract

Inverse Synthetic Aperture Radar (ISAR) can obtain images of targets with high resolution under the condition of all-time, all-weather and long-distance, thus ISAR is of great value in both military and civil application areas. In order to improve the resolution of the images, super-resolution imaging algorithms have broken through the Rayleigh limit and have been widely employed in ISAR imaging. Firstly, this paper summarizes the development and present status of super-resolution imaging algorithms systematically. Secondly, five types of widely used super-resolution ISAR imaging algorithms are briefly introduced: extrapolation methods, nonlinear filtering methods, spectrum estimation methods, matrix pencil methods and sparse imaging methods. Finally, the potential problems and future works of super-resolution ISAR imaging algorithms are discussed.