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Improved Image Reconstruction from Sub-apertures of Circular Spotlight SAR

机译:改进的圆形聚光SAR子孔径图像重建

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Reconstructing images from SAR returns is usually a time consuming task. In addition it is often desired to use as many returns as possible to achieve better image quality. However, the high computational resources demand by the conventional methods hinders the reconstruction process. In this article, we propose a simple method to reconstruct SAR image that is built upon the back-projection algorithm using multiple sub-aperture imagery to attain both greater processing efficiency and improved image quality. Instead of aggregating all the available pulses into one single image following the back-projection algorithm, our proposed method creates multiple SAR image reconstructions from a relatively small number of pulses to exploit variations in sub-aperture views of the scene. The heterogeneity among these sub-aperture views exhibits an exceptional difference between various objects and presents a reconstruction with much less noise. Our proposed method is evaluated with circular spotlight GOTCHA data sets and it demonstrates much improved computational performance and image quality compared to the conventional back-projection algorithm.
机译:从SAR返回信号重建图像通常是一项耗时的任务。另外,通常期望使用尽可能多的返回来获得更好的图像质量。然而,常规方法对计算资源的高需求阻碍了重建过程。在本文中,我们提出了一种简单的重建SAR图像的方法,该方法基于使用多个子孔径图像的反投影算法来获得更高的处理效率和更高的图像质量。我们提出的方法不是按照反投影算法将所有可用脉冲聚集到单个图像中,而是从相对较少的脉冲中创建了多个SAR图像重建,以利用场景子孔径视图的变化。这些子光圈视图之间的异质性在各种对象之间表现出出乎意料的差异,并且呈现出噪声少得多的重建。我们提出的方法是通过圆形聚光灯GOTCHA数据集进行评估的,与传统的反投影算法相比,该方法展示了大大提高的计算性能和图像质量。

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