相位梯度自聚焦在FFBP聚束SAR处理中的应用

发布时间：2018-05-19 23:27

本文选题：改进快速分解后向投影 + 虚拟极坐标系　；参考：《西安电子科技大学学报》2014年03期

【摘要】：基于孔径分解和图像递归融合的快速分解后向投影算法具备接近频域算法的运算复杂度和媲美后向投影算法的聚焦性能.与频域成像算法不同,使用快速分解后向投影算法重建的直角坐标系图像或极坐标系图像均无法满足传统自聚焦方法的使用条件.为了解决这个问题,在原快速分解后向投影算法的基础上创新地引入了虚拟极坐标系,提出了改进快速分解后向投影算法,为自聚焦处理提供图像域与距离压缩相位历程域之间的傅里叶变换对关系.其次,建立全新的重叠子孔径构型,提出了嵌套多孔径相位梯度自聚焦的改进快速分解后向投影算法.最后,利用X波段聚束合成孔径雷达实测数据对该方法进行了验证.
[Abstract]:The fast decomposing backward projection algorithm based on aperture decomposition and image recursive fusion has the same computational complexity as the frequency domain algorithm and the focusing performance of the backward projection algorithm. Different from the frequency domain imaging algorithm, the images of rectangular coordinate system or polar coordinate system reconstructed by fast decomposing backward projection algorithm can not meet the requirements of the traditional self-focusing method. In order to solve this problem, the virtual polar coordinate system is introduced on the basis of the original fast decomposition backward projection algorithm, and an improved fast decomposition backward projection algorithm is proposed. The relation of Fourier transform pair between image domain and range compression phase history domain is provided for self-focusing processing. Secondly, a new overlapping sub-aperture configuration is established, and an improved fast decomposition backward projection algorithm based on nested multi-aperture phase gradient autofocus is proposed. Finally, the method is verified by the measured data of X-band Spotlight synthetic Aperture Radar (SAR).
【作者单位】：西安电子科技大学雷达信号处理国家重点实验室;
【基金】：国家自然科学基金优秀青年基金项目资助(61222108)
【分类号】：TN957.52

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