LAUSR

In synthetic aperture radar (SAR), due to the characteristics of squint data in spaceborne imaging geometry, a more accurate range cell migration correction operation is necessary. Furthermore, imaging degradation due to ignoring range-variant filtering needed for secondary range compression limits SAR imaging. In addition, owing to enormous computational complexity required for squint SAR data processing, the existing imaging methods, for instance, chirp scaling algorithm and range Doppler algorithm, are no longer sufficient, especially for large-scale scenes. In order to solve above problems, this article presents a novel spaceborne squint SAR sparse imaging method, which could not only eliminate the effects of squint to a certain extent, but also improve the performance of focused SAR image. Compared with the matched-filtering-based squint imaging algorithm, the proposed method can obtain the SAR images with higher quality from fully sampled or downsampled echo data.