Robust ISAR Autofocus for Nonuniformly Rotating Target

When a target undergoes complex maneuvers, the resulting inverse synthetic aperture radar (ISAR) image will exhibit significant distortion due to the nonuniform rotational motion. To address this issue, we present a highly effective ISAR autofocus in forming an ISAR image of a nonuniformly rotating target. A novel approach to ISAR imaging for nonuniformly rotating target is presented, utilizing the minimization of collision entropy of ISAR image to simultaneously estimate rotational velocity, rotational acceleration, and rotation center of the target. The efficient Gauss–Newton method along with a newly designed objective function allows for obtaining all parameters effectively. A notable benefit of the proposed autofocus is its independence from any prior information regarding the rotation center of target. Based on the experimental results using the simulated and measured datasets, it can be inferred that the proposed autofocus is remarkably effective in forming ISAR image of a nonuniformly rotating target, achieving computational efficiency and high image quality.