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Developments in LFM-CW SAR for UAV Operation.

机译:用于无人机操作的LFM-CW SAR的发展。

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摘要

Opportunities to use synthetic aperture radar (SAR) in scientific studies and military operations are expanding with the development of small SAR systems that can be operated on small unmanned air vehicles (UAV)s. While the nimble nature of small UAVs make them an attractive platform for many reasons, small UAVs are also more prone to deviate from a linear course due autopilot errors and external forces such as turbulence and wind. Thus, motion compensation and improved processing algorithms are required to properly focus the SAR images. The work of this dissertation overcomes some of the challenges and addresses some of the opportunities of operating SAR on small UAVs.;Several contributions to SAR backprojection processing for UAV SARs are developed including: 1. The derivation of a novel SAR backprojection algorithm that accounts for motion during the pulse that is appropriate for narrow or ultra-wide-band SAR. 2. A compensation method for SAR backprojection to enable radiometrically accurate image processing. 3. The design and implementation of a real-time backprojection processor on a commercially available GPU that takes advantage of the GPU texture cache. 4. A new autofocus method that improves the image focus by estimating motion measurement errors in three dimensions, correcting for both amplitude and phase errors caused by inaccurate motion parameters. 5. A generalization of factorized backprojection, which we call the Dually Factorized Backprojection method, that factorizes the correlation integral in both slow-time and fast-time in order to efficiently account for general motion during the transmit of an LFM-CW pulse.;Much of this work was conducted in support of the Characterization of Arctic Sea Ice Experiment (CASIE), and the appendices provide substantial contributions for this project as well, including: 1. My work in designing and implementing the digital receiver and controller board for the microASAR which was used for CASIE. 2. A description of how the GPU backprojection was used to improved the CASIE imagery. 3. A description of a sample SAR data set from CASIE provided to the public to promote further SAR research.
机译:随着小型合成孔径雷达系统的发展,可以在小型无人飞行器(UAV)上运行的科学研究和军事行动中使用合成孔径雷达(SAR)的机会正在扩大。尽管小型无人机的敏捷特性使它们成为吸引人的平台有很多原因,但由于自动驾驶误差和湍流和风等外力,小型无人机也更倾向于偏离线性航向。因此,需要运动补偿和改进的处理算法来正确聚焦SAR图像。本文的工作克服了一些挑战,并解决了在小型无人机上运行SAR的一些机会。;发展了对无人机SAR反投影处理的若干贡献,包括:1.推导了一种新颖的SAR反投影算法,该算法可解决脉冲期间的运动,适合窄或超宽带SAR。 2.一种用于SAR反投影的补偿方法,以实现辐射精确的图像处理。 3.在商用GPU上利用GPU纹理缓存的实时反投影处理器的设计和实现。 4.一种新的自动聚焦方法,它通过估计三个维度的运动测量误差来改善图像聚焦,同时校正由不正确的运动参数引起的幅度和相位误差。 5.归因化反投影的泛化,我们称为双重因数分解的反投影方法,该方法对慢时和快时的相关积分进行因式分解,以便在LFM-CW脉冲传输期间有效地考虑一般运动。这项工作大部分是为了支持北极海冰实验的特征(CASIE)而进行的,附录也为该项目提供了实质性的贡献,包括:1.我在设计和实施数字接收器和控制器板上的工作。用于CASIE的microASAR。 2.描述了如何使用GPU反投影来改善CASIE图像。 3.描述了CASIE提供给公众的SAR数据样本集,以促进SAR的进一步研究。

著录项

  • 作者

    Stringham, Craig.;

  • 作者单位

    Brigham Young University.;

  • 授予单位 Brigham Young University.;
  • 学科 Electrical engineering.;Computer engineering.;Remote sensing.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 138 p.
  • 总页数 138
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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