| 陈 潜,刘金清.结合属性散射中心模型和空间变
迹法的 SAR 图像旁瓣抑制方法[J].电子测量与仪器学报,2020,34(10):178-185 |
| 结合属性散射中心模型和空间变
迹法的 SAR 图像旁瓣抑制方法 |
| Depression of SAR image sidelobes based on combination of attributed scattering center model and spatially variant apodization |
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| DOI： |
| 中文关键词: 合成孔径雷达 空间变迹法 属性散射中心模型 参数估计 旁瓣抑制 |
| 英文关键词:synthetic aperture radar ( SAR) spatially variant apodization ( SVA) attributed scattering center parameter estimation sidelobe depression |
| 基金项目:福建省基金(2017J01464)资助项目 |
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| 中文摘要: |
| 针对合成孔径雷达( synthetic aperture radar,SAR) 图像旁瓣抑制问题,提出结合属性散射中心模型和空间变迹法
(spatially variant apodization, SVA)的新途径。 空间变迹法作为一种经典超分辨率图像处理技术,能在抑制旁瓣的同时保持良
好的主瓣分辨率。 属性散射中心可以很好地描述目标在高频区的电磁散射特性,是分析 SAR 图像的有力工具。 基于属性散射
模型的参数估计得到的先验知识再利用空间变迹法处理 SAR 图像,达到抑制旁瓣的目的。 实验结果表明,该方法可以有效抑
制 SAR 图像旁瓣。 |
| 英文摘要: |
| For the problem of depression of the high sidelobes in synthetic aperture radar (SAR) images, a new way based on attributed
scattering center model and spatially variant apodization ( SVA) is proposed. SVA is one of the classical super-resolution image
processing technologies, which could keep the resolution of mainlobe while depressing the sidelobes. Attributed scattering center can
properly depict the scattering properties of targets at high frequency region, which is an important tool to analyze the SAR image.
Attributed scattering center is employed to do the parameter estimation and then the parameters are used to do the SVA filter.
Experimental show that the effectiveness of the proposed method as for depressing the sidelobes. |
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