一种非均匀转动目标的ISAR自聚焦算法

在ISAR成像中,目标的非均匀转动会引入与散射点位置有关相位误差,无法用统一的相位误差函数表示,因此通常的自聚焦方法难以消除。针对加速转动目标,本文提出了一种基于离散调频傅立叶变换(discrete chirp-Fourier trans- form)的自聚焦算法。在预先选定的距离单元上,利用离散调频傅立叶变换提取最大功率散射点对应的调频信号,并以之为参考信号消除目标平动引起的相位误差。然后,利用同样的方法,在多个距离单元上提取最大功率散射点对应的调频信号,根据该散射点信号估计目标非均匀转动的参数,并进行非均匀采样,去除非均匀转动的相位误差。将该算法应用于仿真试验和实测数据的ISAR成像中,都得到了较好的聚焦结果。

An ISAR Autofocus Algorithm for the Target with Nonuniform Rotation

When the inverse synthetic aperture radar(ISAR)imaging the target with nonuniform rotations,the phase errors de- pend on scatters positions.Such phase errors can not be eliminated through conventional autofocus algorithms.An autofocus algorithm based on the discrete chirp-Fourier transform(DCFT)is proposed to image the accelerating targets.In this algorithm,by applying DCFT on the signal in the selected range bin,the scatter signal with maximum energy is extracted.Taking this selected scatter signal as the ref- erence signal,the translational phase errors are removed.Then,with the same method,the scatter signals with maximum energy are also extracted on several selected range bins.And the phase errors caused by nonuniform rotation are also compensated through estimating the rotation parameters and nonuniform sampling.Experimentations with the simulated and measured ISAR data demonstrate the effectiveness of the autofocus algorithm.