A Nonparametric Translational Motion Compensation Algorithm for ISAR Imaging by Using the Alternating Iteration and LBFGS Algorithm

A translational motion compensation method for a target with non-parametric translation in dechirping system is proposed in this paper. We establish the non-parametric translational motion compensation scheme based on the optimization of an image's sharpness. Since the impacts of the range shifts and phase errors on an image's quality are different, we convert the optimization into an alternating iteration of estimating two vectors. These two kinds of iterations are searching for range shifts and phase errors for each range profile, respectively. The Limited-Memory BFGS algorithm is used to solve the optimization problems with high efficiency. According to the application of the proposed algorithm to the real data, it is valid and could be faster and be of higher performance in comparison with some existing methods.