ISAR autofocus by minimizing entropy of eigenimages

In this paper, we propose a novel and efficient inverse synthetic aperture radar (ISAR) autofocus technique by applying an eigenimage with a preprocessing step to minimum entropy phase adjustment (MEPA) algorithm. Several experimental results using measured data of an actual flying aircraft demonstrated that the proposed scheme can lead to substantially fast convergence to global minimum of the entropy cost surface and reduce the computational complexity of ISAR autofocus, compared to the traditional MEPA.