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Wavenumber-Domain Autofocusing for Highly Squinted UAV SAR Imagery

机译:高斜视无人机SAR图像的波数域自动聚焦

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摘要

Being capable of enhancing the flexibility and observing ability of synthetic aperture radar (SAR), squint mode is one of the most essential operating modes in SAR applications. However, processing of highly squinted SAR data is usually a challenging task attributed to the spatial-variant range cell migration over a long aperture. The Omega-k algorithm is generally accepted as an ideal solution to this problem. In this paper, we focus on using the wavenumber-domain approach for highly squinted unmanned aerial vehicle (UAV) SAR imagery. A squinted phase gradient autofocus (SPGA) algorithm is proposed to overcome the severe motion errors, including phase and nonsystematic errors. Herein, the inconsistence of phase error and range error in the squinted wavenumber-domain imaging is first presented, which reveals that even the motion error introduces very small phase error, it causes considerable range error due to the Stolt mapping. Based on this, two schemes of SPGA-based motion compensation are developed according to the severity of motion error. By adapting the advantages of weighted phase gradient autofocus and quality phase gradient autofocus, the robustness of SPGA is ensured. Real measured data sets are used to validate the proposed approach for highly squinted UAV-SAR imagery.
机译:斜视模式能够增强合成孔径雷达(SAR)的灵活性和观察能力,是SAR应用中最重要的操作模式之一。但是,处理高度斜视的SAR数据通常是一项具有挑战性的任务,这归因于空间变化范围内的单元在长孔径上的迁移。 Omega-k算法通常被认为是解决此问题的理想解决方案。在本文中,我们专注于将波数域方法用于高度斜视的无人机(UAV)SAR图像。为了克服严重的运动误差,包括相位误差和非系统误差,提出了斜视相位梯度自动聚焦算法。本文首先介绍了斜波数域成像中的相位误差和距离误差的不一致性,这表明即使运动误差也引入了很小的相位误差,但由于Stolt映射会引起相当大的距离误差。在此基础上,根据运动误差的严重程度,提出了两种基于SPGA的运动补偿方案。通过利用加权相位梯度自动聚焦和质量相位梯度自动聚焦的优势,可以确保SPGA的鲁棒性。实际测量的数据集用于验证针对高斜视UAV-SAR图像的建议方法。

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  • 来源
    《Sensors Journal, IEEE》 |2012年第5期|p.1574-1588|共15页
  • 作者

    Lei Zhang;

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