LASAR autofocus imaging using maximum sharpness back projection via semidefinite programming

Linear array SAR (LASAR) three-dimensional (3-D) is a promising 3-D radar imaging technology. As several antenna phase centers (APCs) activity in one pulse repetition time (PRT) simultaneously, it is very difficult to compensate the motion errors of these APCs using navigation data (e.g. inertial measuring unit and global positioning system) only. In this paper, a novel autofocus algorithm is proposed for LASAR 3-D imaging by exploiting maximum sharpness back projection via semidefinite programming. In the scheme, an iterative method aims to maximizing the LASAR image sharpness, was derived to obtain the phase errors of the APCs. Moreover, to improve computational efficacy, only the dominant scatterers were selected as the input of the phase-error estimation. The effectiveness of the algorithm is demonstrated with both simulation and experimental examples.