基于FRFT的非均匀转动目标ISAR自聚焦算法

Novel ISAR Autofocus Algorithm for the Target with Non-uniform Rotation Based on Fractional Fourier Transform

在ISAR成像中,目标的非均匀转动会引入与散射点位置有关的相位误差,无法用统一的相位误差函数表示,而散射点子回波的相位精度对于ISAR自聚焦的相位校正非常重要.针对加速转动的目标,提出了一种基于分数阶傅里叶变换(FRFT:fractional Fourier transform)的自聚焦算法.在预先选定的距离单元上,利用分数阶傅里叶变换提取最大功率散射点对应的调频信号,并以该信号为参考信号消除目标平动引起的相位误差.利用同样的方法,在多个距离单元上提取最强散射点对应的调频信号,并对调频信号的估计值加权平均,得到非均匀转动参数的最优估计,进而对信号非均匀采样,消除非均匀转动的相位误差.仿真结果验证了该算法能够很好地消除相位误差.

In the inverse synthetic aperture radar （ISAR） imaging, the non-uniform rotation of the targets can bring phase errors relevant to scatters＇ positions. The phase errors can not be expressed by one uniform function. But the scat- ters＇ phase precision is very important to phase emendation of ISAR＇s autofocus. For the accelerating targets, an autofo- cus algorithm based on fractional Fourier transform （FRFT） is proposed. FRCFT is applied to process the signals in the selected range unit, and extract the scatter＇s signal with the maximum energy, this selected scatter signal is taken as the reference signal to eliminate the plane motion phase errors. By the same method, the scatters＇ signals with maximum en- ergy are also extracted on several selected range units. And modulated frequency signals are weighted on the average to get the optimized estimated values of the non-uniform rotation parameters. Based on the parameters, the signals are sampled non-uniformly to eliminate the phase errors. Finally, the simulation results demonstrate that the algorithm can eliminate the phase errors very well.