基于最大锐度半正定规划的线阵SAR自聚焦三维成像

线阵合成孔径雷达（LASAR）三维成像技术是一种具有重要潜在应用价值的新型雷达成像技术。但在一个脉冲重复时间中，LASAR系统中需采用阵列天线多个天线相位中心同时接收回波，仅利用载荷单个测量位置的导航测量系统（如惯性测量系统或全球定位系统）数据难以精确补偿LASAR阵列天线多个相位中心的运动误差。为了克服运动误差对阵列多天线相位中心影响，该文提出了一种基于最大锐度半正定规划的LASAR后向投影自聚焦成像算法。该算法建立了后向投影成像算法处理的线性数学模型，结合LASAR三维图像锐度最大化原则，利用迭代逼近最优方法对阵列多天线相位中心运动误差引入的相位误差进行估计。另外，为了提高自聚焦算法运算效率，仅采用主散射目标区域进行相位误差估计。仿真数据和实测数据验证了该算法的有效性。

Linear Array SAR Autofocus 3-D Imaging via Maximum Sharpness Semidefinite Programming

Linear array synthetic aperture radar (LASAR) three-dimensional (3-D) imaging technology is a promising innovative 3-D radar imaging technology. As several antenna phase centers (APCs) activity in one pulse repetition time (PRT) simultaneously, it is very difficult to accurately compensate the motion errors of these APCs using navigation measurement 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, the linear mathematical model of back projection algorithm processing is set up, an iterative method aiming to maximize the LASAR image sharpness is derived to obtain the motion errors of the APCs. Moreover, to improve computational efficacy, only the dominant scatterers are selected as the input of the phase-error estimation. The effectiveness of the algorithm is demonstrated with both simulation and experimental examples.