Phase compensation in ISAR imaging: comparison between maximum likelihood-based approach and minimum entropy-based approach

摘要

Inverse synthetic aperture radar (ISAR) imaging is a powerful tool in microwave imaging for moving targets. In this paper, an analysis and comparison between maximum likelihood-based and minimum entropy-based approaches for phase compensation in ISAR imaging have been carried out. Moreover, real ISAR data processing is presented and some results like the autofocusing effect, computation complexity and convergence performance are discussed.