Sidelobe Suppression of Squinted SAR Complex Data Based on Minimum Image Sharpness

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-04-11 DOI:10.1109/LGRS.2025.3560202

Yanfang Liu;Wei Yang;Hongcheng Zeng;Haijun Shen;Yamin Wang;Xiaojie Zhou;Chunsheng Li

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Abstract

Sidelobe suppression is of particular importance in the synthetic aperture radar (SAR) image quality improvement. However, the range and azimuth sidelobes are coupled and non-orthogonal in squinted SAR images, which makes traditional methods ineffective. This letter presents a sidelobe suppression method for squinted SAR complex data based on the SAR convolution model and minimum image sharpness. First, the convolution model of SAR images is revised with the subpixel offset. Then, the sidelobe suppression is achieved by deconvolution pixel by pixel. Innovatively, a convex optimization based on minimum image sharpness is built and solved to estimate the unknown and variant subpixel offset of each target. In addition, a new factor based on integrated sidelobe ratio (ISLR) is applied for efficiency improvement. Finally, results on the squinted spaceborne SAR real data verify the effectiveness of the proposed method both in sidelobe suppression and the maintenance of amplitude-phase characteristics. The codes are available in https://github.com/Keyserliu/Sidelobe-Suppression

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基于最小图像清晰度的斜视SAR复杂数据旁瓣抑制

副瓣抑制在提高合成孔径雷达（SAR）图像质量中具有重要意义。然而，在斜视SAR图像中，距离副瓣和方位角副瓣是耦合且非正交的，使得传统的方法效果不佳。本文提出了一种基于SAR卷积模型和最小图像清晰度的斜视SAR复合数据旁瓣抑制方法。首先，利用亚像素偏移量对SAR图像的卷积模型进行修正。然后，通过逐像素反卷积实现副瓣抑制。创新地，建立并解决了基于最小图像清晰度的凸优化，以估计每个目标的未知和可变亚像素偏移。此外，为了提高效率，还引入了一种基于综合旁瓣比（ISLR）的新因子。最后，在斜视星载SAR实际数据上验证了该方法在抑制副瓣和保持幅相特性方面的有效性。代码可在https://github.com/Keyserliu/Sidelobe-Suppression上获得

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IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society

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