基于多脉冲联合估计的SAR相位误差自聚焦算法

Phase error autofocus algorithm for spotlight SAR imagery using multiple-pulse vectors

合成孔径雷达(synthetic aperture radar,SAR)是相干成像系统,所以接收信号相位的正确性决定了SAR图像的聚焦质量。利用自聚焦算法对SAR图像进行相位误差函数的估计及补偿是获得高分辨率,高质量SAR图像的关键步骤之一。其中,相位梯度自聚焦(phase gradient autofocus,PGA)算法运算量适中且鲁棒性好,被广泛应用于SAR自聚焦中。然而,PGA算法基于相位误差梯度值进行加权平均估计,相位差分的过程会引起噪声的积累,因此该算法对原SAR图像在方位数据域的信噪比要求较高。针对PGA算法存在问题,提出了基于多脉冲联合估计的相位误差自聚焦(phase error autofocus,PEA)算法。该算法采用了PGA算法的处理结构,并基于相位误差直接进行加权平均估计,可以在较低信噪比条件下正确实现SAR图像的自聚焦处理。仿真实验以及实测数据处理结果对比均表明,PEA算法可以获得优于PGA算法的自聚焦性能,且实际算法执行时间更短,更有利于算法实时处理。

For synthetic aperture radar （SAR） is a coherent imaging system, signal based phase error cor- rection, i. e. , autofocus of SAR imagery is an important technique to improve the azimuth focusing quality. A variety of autofocus algorithms exist for generating high quality and high resolution SAR imagery. Among them, phase gradient autofocus （PGA） employs adjacent pulses of the range-compressed data as inputs to estimate the gradient of phase error at each position of the aperture, which is most widely used in practice for its efficient re- alization and excellent robustness. However, the precision of PGA would be severely affected by the signal-to- noise ratio of the input range lines. In order to solve this problem, a novel autofocus algorithm called phase er- ror autofocus is presented, which could estimate the phase error directly by multiple-pulse vectors. Monte Carlo tests and real SAR data validate that the new approach could achieve better performance of autofocus in SAR im- ages with lower levels of the execution time than PGA.