旋转扫描地基SAR大视场快速成像算法
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  • 英文篇名:The Large Field of View Fast Imaging Algorithm for Arc Synthetic Aperture Radar
  • 作者:林赟 ; 宋扬 ; 王彦平 ; 李洋
  • 英文作者:Lin Yun;Song Yang;Wang Yanping;Li Yang;School of Information Science and Technology, North China University of Technology;
  • 关键词:合成孔径雷达(SAR) ; 地基合成孔径雷达(GBSAR) ; 旋转扫描地基合成孔径雷达(ArcSAR) ; 快速成像算法
  • 英文关键词:synthetic aperture radar(SAR);;ground based SAR(GBSAR);;Arc synthetic aperture radar(ArcSAR);;fast imaging algorithm
  • 中文刊名:XXCN
  • 英文刊名:Journal of Signal Processing
  • 机构:北方工业大学信息学院;
  • 出版日期:2019-03-25
  • 出版单位:信号处理
  • 年:2019
  • 期:v.35;No.235
  • 基金:国家重点研发计划(2018YFC1505103);; 国家自然科学基金重点国际合作研究项目(61860206013);国家自然科学基金面上项目(61571421);; 北京市自然科学基金(4192019)
  • 语种:中文;
  • 页:XXCN201903023
  • 页数:8
  • CN:03
  • ISSN:11-2406/TN
  • 分类号:187-194
摘要
旋转扫描地基合成孔径雷达(ArcSAR)具备高分辨率、大视场、重访周期短等优势,因此近年来受到越来越多的关注并逐渐被应用于地面形变监测。该系统特殊的运动轨迹(弧线)增加了成像算法难度。虽然时域算法能够获取ArcSAR高精度的成像结果,但时域算法计算效率较低。因此本文提出一种新的针对ArcSAR的频域成像算法。首先给出了ArcSAR的几何模型以及信号模型。然后论述了算法原理,并对二维频域匹配滤波器进行了推导。之后对算法的适用条件进行讨论。最后利用仿真实验对算法的适用条件进行验证,并对时域成像算法和本文提出的快速成像算法的成像效率和成像质量进行比较。
        ArcSAR has the advantages of high resolution, large field of view, and short revisit period. Therefore, it receives more and more attention in the scientific literature in recent years and is gradually applied to ground monitoring. The complex motion trail(arc) of the ArcSAR increases the difficulty of the imaging algorithm. Although the time domain algorithm can obtain high-precision imaging results of the system, this type of algorithm is computationally inefficient. Therefore, this paper proposes a novel fast imaging algorithm for ArcSAR. Firstiy, the geometric model and signal model of ArcSAR are given. Then the principle of the algorithm is discussed and the two-dimensional frequency domain matched filter is deduced. Besides, the applicable condition of the algorithm is also discussed. Finally, the application condition of the proposed algorithm are verified by simulation experiments, and the imaging efficiency and imaging quality of the time domain imaging algorithm and the fast imaging algorithm proposed in this paper are compared.
引文
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