可结合CSAR时域成像处理的改进PGA方法

以后向投影算法（Back Projection, BP）为代表的时域类成像算法能够适用于复杂轨迹下的雷达图像重建，且具有精确成像能力。然而，这类算法的成像过程往往不满足结合传统自聚焦算法的条件，从而限制了其对实测数据的成像性能。针对这个问题，本文提出了一种可结合圆周合成孔径雷达（Circular Synthetic Aperture Radar, CSAR）时域成像处理的改进相位梯度自聚焦算法（Phase Gradient Autofocus, PGA）。首先，基于CSAR的成像几何，推导了运动误差形式；在此基础上建立了运动误差条件下的BP成像处理信号模型；接下来，提出了可结合CSAR时域成像处理的改进PGA算法，并给出了详细的处理流程；最后，利用实测数据成像处理结果证明了理论分析的正确性和所提算法的有效性。 

The phase gradient autofocus approach for time-domain method of circular SAR

Time-domain algorithm, such as back projection (BP), can deal with SAR imagery precisely with complicated radar trajectory. However, SAR images reconstructed by time-domain algorithm cannot satisfy the requirements of conventional autofocus method, which constrains the performance of time-domain algorithm in practical situation. To solve the problem, we propose an improved PGA approach which can be embedded into time-domain algorithm for processing circular SAR (CSAR) data. Firstly, based on the imaging geometry of CSAR, the of the motion error encountered in CSAR is presented, and on this basis, the signal formation of back projection is derived. Then, the implementation of improved PGA is presented in detail. Finally, the real data experiment is processed, and the results prove the correctness of the theory analysis and the validity of the proposed approach.