基于先验知识的SAR两维自聚焦算法

Prior Knowledge Aided Two Dimensional Autofocus Approach for Synthetic Aperture Radar

传统的SAR(Synthetic Aperture Radar)两维自聚焦算法没有充分挖掘残留相位误差所特有的内部结构信息,是对残留相位误差的一种盲估计,实际应用时在估计精度和计算效率等方面还受到一定限制.本文以极坐标格式算法为例,详细分析了成像算法处理后残留两维相位误差的解析结构,并利用这种先验辅助知识,提出了一种基于—维估计/两维校正的自聚焦算法.算法只需直接估计方位一维相位误差,然后利用两维相位误差内部所特有的结构信息,将一维相位误差映射得到两维相位误差,从而实现精确的两维自聚焦.实测数据处理结果验证了本文算法的有效性.

Conventional two dimensional（2D） autofocus algorithms didn＇t take advantage of the priori information on the structure of phase error.They often suffered from lack of redundancy to accurately estimate the 2D phase error.In this paper,a knowledge aided（KA）2D autofocus approach is presented,which is based on exploiting the priori knowledge on the phase error structure.First,as a prerequisite for the proposed KA method,the analytical structure of residual 2D phase error in SAR（Synthetic Aperture Radar）imagery is investigated in the polar format algorithm framework.Then,by incorporating this prior information,a 2D autofocus approach is proposed.The new method only requires an estimate of azimuth 1D phase error,while the 2D phase errors can then be computed directly from the estimated azimuth phase error.Experimental results indicate the effectiveness of the proposed method.