Joint random stepped frequency ISAR imaging and autofocusing based on 2D alternating direction method of multipliers

Abstract

Random stepped frequency (RSF) inverse synthetic aperture radar (ISAR) has attracted more attention due to its outstanding electronic counter-countermeasure (ECCM) performance by frequency agility. However, the two-dimensional (2D) sparse sampling echo, i.e. sparse sub-pulses and sparse aperture, increases the difficulty of 2D high-resolution ISAR imaging and autofocusing. Aiming to solve this problem, a novel 2D alternating direction method of multipliers (2D-ADMM) based imaging and autofocusing framework is proposed to achieve 2D high-resolution for 2D sparse RSF ISAR. In order to obtain the optimal value for phase correction, the phase error corresponding to each sub-pulse is estimated by solving an unconstrained optimization problem. To jointly achieve autofocusing during the process of ISAR image reconstruction, the phase error estimation is merged into the image reconstruction framework, and then two different strategies under the 2D ADMM framework are derived to iteratively solve this compound optimization problem in matrix form. Experiments based on both simulated and measured data validate the effectiveness of the proposed 2D joint methods, meanwhile, maintaining an acceptable imaging efficiency.