In the scanning synthetic aperture radar (ScanSAR) mode, the radar antenna sweeps through different range subswaths to image a wide swath. The full-aperture imaging algorithm for ScanSAR data has been widely used because it can be realized by exploiting the existing standard high-precision Stripmap SAR processor and does not require stitch processing in the azimuth. However, both the focused image and the interferogram achieved by full-aperture processing suffer from spikes. The spikes adversely affect the ScanSAR-related applications, such as target detection and interferometry. To effectively suppress the spikes, an improved algorithm based on the missing-data iterative adaptive approach (MIAA) is proposed in this manuscript. Besides, the proposed method can also improve the azimuth resolution of ScanSAR images. Simulation and experimental results demonstrate that this algorithm has better performance when processing ScanSAR data compared with existing methods.

中文翻译：

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集成基于MIAA的孔径插值的改进的全孔径ScanSAR成像方法

在扫描合成孔径雷达（ScanSAR）模式下，雷达天线会扫过不同范围的子带，以成像大范围的地带。由于可以通过利用现有的标准高精度Stripmap SAR处理器来实现，并且不需要方位角中的针脚处理，因此ScanSAR数据的全孔径成像算法已被广泛使用。但是，通过全光圈处理获得的聚焦图像和干涉图均会出现尖峰。尖峰会对与ScanSAR相关的应用产生不利影响，例如目标检测和干涉测量。为了有效地抑制尖峰信号，本文提出了一种基于丢失数据迭代自适应方法（MIAA）的改进算法。此外，该方法还可以提高ScanSAR图像的方位分辨率。