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Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging

机译:广义线性调频缩放与基带方位角缩放算法相结合的大带宽滑动聚光SAR成像

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摘要

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm.
机译:本文提出了一种高效,精确的大带宽滑动聚光合成孔径雷达(SAR)成像算法。现有的基于基带方位角缩放(BAS)算法的子孔径处理方法无法应对沿距离和方位角方向的高阶相位耦合。该耦合问题导致沿范围和方位角方向散焦。提出了一种基于GCS算法的广义线性调频缩放-BAS处理算法。它成功地缓解了大带宽滑动聚光灯SAR子孔径沿范围尺寸的深度聚焦,以及沿范围和方位尺寸的高阶相位耦合。另外,可以通过这种方位缩放方法来实现方位聚焦。仿真结果表明,GCS-BAS算法具有处理大带宽滑动聚光SAR数据的能力。事实证明,通过GCS-BAS算法,可以大大提高聚焦深度和成像精度。

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