一种基于高阶统计量的SAR图像自聚焦算法

 提出了一种基于高阶统计量分析的相位误差估计算法,用于SAR 图像自聚焦。该算法从复图像域出发,通过循环移位及加窗处理孤立强点目标,利用高阶累积量对高斯噪声的抑制能力,在距离压缩相位历史域估计相位误差。由于避免了对加性噪声及干扰很敏感的差分运算,相位误差的估计结果有很好的鲁棒性。仿真及实测数据的处理结果证明了该算法的可行性。

New Algorithm Based on Higher-Order Statistics for SAR Imagery Autofocus

In this paper, a new method of phase errors estimation based on higher order statistics is proposed for SAR imagery autofocus. The method, which starts right in with complex phase degraded SAR imagery, isolates the dominant point target in the image domain via circular shifting and windowing, and then estimates phase errors in the range compressed phase history domain by a higher order cumulant. The algorithm makes good use of the property that the higher order cumulant can suppress noise with Gaussian distribution, while avoiding derivative computation which can be sensitive to additive noise and disturbance. So the phase errors estimation will be more robust. Simulation and processing results of real data show the feasibility of the proposed method.