一种改进的组合实时自聚焦算法

在高分辨率SAR中，方位向运动误差给成像带来的影响越来越大，传统的相位梯度自聚焦(PGA)方法能够估计出运动误差，但其需要多次迭代计算，计算量大，不适合用于实时成像。为了满足高分辨率SAR实时成像的需求，提出了一种改进的组合实时PGA方法。这种方法将改进的频移相关算法(ISAC)算法、 PGA算法与RD成像算法结合运用，不仅使计算量大大减少，而且通过在频移相关算法中加入适量的迭代运算，降低了对运动初始参数的精度要求，取得了较好的成像效果。理论分析和实际数据处理证明了这种方法的有效性。

Improved combined real time autofocus algorithm

In the high resolution SAR, the effect of motion error at the azimuth direction is more severe. Though the traditional Phase Gradient Autofocus (PGA) algorithm can be used to estimate the motion error, the iterative phase correction has to be done. The huge computation makes it difficult to be used in real time image processing. In order to meet the request of real time imaging of high resolution SAR, the Iterative Shift And Correlate (ISAC) algorithm, PGA algorithm and Range Doppler (RD) algorithm are combined in this paper. With the new combined algorithm, the iterative operation can be reduced. At the same time, the precision request for the initial motion parameter is decreased by adding appropriate iterations to the Shift And Correlate (SAC) algorithm. The theoretical analysis and the result of imaging for real SAR data can validate the new algorithm.