Phase compensation for ISAR imaging combined with entropy principle

Inverse synthetic aperture radar (ISAR) imaging is a powerful tool in microwave imaging for moving target. It provides high range resolution by transmitting wide-band signal, and high cross-range resolution by coherently accumulating echoes, where phase compensation is one core technique for range-Doppler image formation. However, conventional phase compensation methods usually have problems to compensate the translational motion between radar and target with sufficient accuracy when the motion has high order or even random terms. To solve this problem, the minimum entropy idea is introduced in this paper for ISAR imaging via a nonparametric estimation method.