通过傅立叶系数的距离-多普勒处理:到达亚奈奎斯特SAR的路径

Kfir Aberman, Yonina C. Eldar
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引用次数: 3

摘要

随着对宽幅、高分辨率合成孔径雷达(SAR)图像需求的不断增长,对高采样率的要求越来越高,而这在实际应用中很难实现。因此,降低采样率在雷达成像中具有很高的实用价值。在本文中,我们引入了一种新的算法,相当于著名的距离-多普勒方法,利用原始信号的傅里叶系数来处理SAR数据。然后,我们演示了如何利用新的算法特征,特别是在距离单元迁移校正(RCMC)之前和之后处理的信号之间的关系,以降低采集阶段的采样率,并以亚奈奎斯特速率有效地处理信号。除了降低采样率外,本文提出的快速恢复算法还形成了一种新的CS-SAR成像方法,可应用于以亚奈奎斯特速率获取的高质量、高分辨率真实SAR成像数据。使用模拟数据集对算法的性能进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Range-Doppler processing via fourier coefficients: The path to a sub-Nyquist SAR
The increasing demand for wide swath, high-resolution, Synthetic Aperture Radar (SAR) images, requires high sampling rates which are difficult to attain in practice. Consequently, sampling rate reduction is of high practical value in radar imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier coefficients of the raw signals. We then demonstrate how to exploit the new algorithm features, particularly, the relationship between the processed signals before and after Range Cells Migration Correction (RCMC), to reduce sampling rate at the acquisition stage and process the signals effectively at sub-Nyquist rates. Beyond sampling rate reduction, the proposed fast recovery algorithm forms a new CS-SAR imaging method that can be applied to high-quality and high-resolution real SAR imaging data acquired at sub-Nyquist rates. The performance of the algorithms is assessed using simulated data sets.
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