基于分数阶傅里叶变换的运动舰船聚焦算法

发布时间：2018-05-24 03:21

本文选题：合成孔径雷达 + 自聚焦　；参考：《电讯技术》2017年05期

【摘要】：为解决合成孔径雷达(SAR)图像中运动舰船目标产生的散焦现象,结合对比度最大算法和分数阶傅里叶变换(FRFT)算法,提出了一种改进的对比度分数阶傅里叶变换(CFRFT)自聚焦算法。该算法利用分数阶傅里叶变换对已成像SAR图像进行时频域分析,根据旋转角分别利用参数模型和非参数模型对二阶相位误差和高阶相位误差进行补偿,和传统的相位梯度(PGA)法相比,图像分辨率和旁瓣比提升显著,可以更有效地补偿SAR中舰船运动产生的相位误差。对不同舰船和尾迹SAR图像实验表明,算法对二阶以上的相位误差具有较好的补偿效果,误差估计准确性高,适用范围广,解决了SAR运动舰船的散焦问题,提高了海洋舰船监测的准确性。
[Abstract]:In order to solve the defocusing phenomenon of moving ship targets in synthetic Aperture Radar (SAR) images, an improved contrast fractional Fourier transform (CFRFT) self-focusing algorithm is proposed by combining the maximum contrast algorithm and the fractional Fourier transform (FRFT) algorithm. The algorithm uses fractional Fourier transform to analyze the SAR image in time-frequency domain, and compensates the second-order phase error and high-order phase error according to the rotation angle by using the parametric model and the non-parametric model, respectively. Compared with the traditional phase gradient method, the image resolution and sidelobe ratio are improved significantly, and the phase error caused by ship motion in SAR can be compensated more effectively. Experiments on SAR images of different warships and wakes show that the algorithm has good compensation effect for phase errors above the second order, and the accuracy of error estimation is high, and the range of application is wide. The defocusing problem of SAR moving ships is solved. The accuracy of ocean ship monitoring is improved.
【作者单位】：复旦大学电磁波信息科学教育部重点实验室;
【基金】：国家自然科学基金资助项目(61179022)
【分类号】：TN957.52

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