电子与控制

一种适用于快速分解后向投影聚束SAR成像的自聚焦方法

  • 李浩林 ,
  • 陈露露 ,
  • 张磊 ,
  • 邢孟道 ,
  • 保铮
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  • 西安电子科技大学 雷达信号处理国家重点实验室, 陕西 西安 710071
李浩林男,博士研究生。主要研究方向:SAR高分辨成像与运动补偿。Tel:029-88201032E-mail:lihaolin322@163.com;陈露露女,硕士研究生。主要研究方向:SAR成像与实时信号处理。张磊男,博士,讲师。主要研究方向:SAR/ISAR高分辨成像与运动补偿。邢孟道男,博士,教授,博士生导师。主要研究方向:雷达成像和目标识别。

收稿日期: 2013-09-27

  修回日期: 2014-04-04

  网络出版日期: 2014-04-10

基金资助

国家自然科学基金(61301280)

An Autofocus Method for Spotlight SAR Imagery Created by Fast Factorized Back-projection

  • LI Haolin ,
  • CHEN Lulu ,
  • ZHANG Lei ,
  • XING Mengdao ,
  • BAO Zheng
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  • National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China

Received date: 2013-09-27

  Revised date: 2014-04-04

  Online published: 2014-04-10

Supported by

National Natural Science Foundation of China (61301280)

摘要

基于孔径分解和图像递归融合的快速分解后向投影(FFBP)算法具备接近频域算法的运算复杂度和媲美后向投影(BP)算法的聚焦性能。但与频域成像算法不同,使用FFBP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,首先,提出了虚拟极坐标系作为FFBP算法的图像重建平面,为自聚焦方法的使用奠定了基础;其次,以基于回波数据的运动补偿为目标,充分利用FFBP算法多孔径递归融合的特点,将多孔径图像偏移(MAM)的相位估计方法嵌套到FFBP算法的各个阶段,从而实现MAM与FFBP算法的紧密相容;最后,通过实测数据处理验证了该方法的可行性和有效性。

本文引用格式

李浩林 , 陈露露 , 张磊 , 邢孟道 , 保铮 . 一种适用于快速分解后向投影聚束SAR成像的自聚焦方法[J]. 航空学报, 2014 , 35(7) : 2011 -2018 . DOI: 10.7527/S1000-6893.2013.0040

Abstract

Fast factorized back-projection (FFBP) is an effective algorithm constructed based on aperture factorized and image recursive fusion. It is shown that the number of operations can be made comparable to frequency domain algorithms and the image quality is barely sacrificed compared with back-projection (BP). Different from frequency domain algorithms, rectangular coordinate system images and polar coordinate system images reconstructed by FFBP cannot satisfy the requirement of traditional autofocus. To solve this problem, we establish a pseudo-polar coordinate system for reconstruction in FFBP firstly, which paves a way for autofocusing method. Secondly, multi-aperture operations are not only performed in FFBP but also are used in multiple aperture mapdrift (MAM), This characteristic becomes a great advantage to incorporate MAM into FFBP iterations seemly and achieve the success of data based motion compensation. Finally, the results of collected data sets validate the feasibility and effectiveness of the proposed approach.

参考文献

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