ISAR Image Resolution Enhancement: Compressive Sensing Versus State-of-the-Art Super-Resolution Techniques

The applicability of compressive sensing (CS) to inverse synthetic aperture radar (ISAR) imagery has been widely discussed over the past few years. In particular, CS-based ISAR image-reconstruction algorithms have been developed and their effectiveness proven when dealing with incomplete ISAR data. Resolution enhancement has also been identified as a case for which CS can be effectively applied to ISAR imagery. In this case, the acquired signal can be interpreted as incomplete data in the frequency/slow-time domain and CS used to reconstruct the super-resolved ISAR image. In this paper, an exhaustive performance analysis is carried out along with a comparison between CS and conventional super-resolution techniques. Several concepts and methods have been introduced in order to effectively define the performance, which is not simply based on visual inspection.

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