An Imaging Method for Ship Target Based on Rotation Parameters Estimation and Extended Nonlinear Chirp Scaling

In this paper, the problem of imaging targets with uniform rotation is investigated, and a solution method based on genetic algorithm and extended nonlinear chirp scaling is proposed. Firstly, the keystone transform and high-order range cell migration are performed to accomplish motion compensation. Then, the differential evolution (DE) algorithm, a mutant of the genetic algorithm, is utilized to search the optimal rotation parameters. In DE algorithm, the image entropy is adopted as the object function. Simulation results validate that the proposed method can estimate rotation parameters accurately and achieve desirable peak side-lobe ratio and integration side-lobe ratio.