雷达目标散射矩阵分解及其在高分辨率目标成像中的应用

E. Krogager
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引用次数: 16

摘要

简要介绍了极化雷达的基本理论和各种分解理论。针对高分辨率成像,提出了一种新的散射矩阵分解方法。通过将散射矩阵分解为三个不同的分量,可以分辨出不同类型的散射体,即使它们在图像的同一分辨率单元内。这允许一个更好的目标散射特性的分辨率,以及一个更好的表征散射类型的个人贡献。通过将这种分解应用于由许多单独散射体组成的复杂目标模型的模拟图像,证明了这种分解的有用性和利用与雷达目标成像有关的全极化数据的一般优势。与单极化数据相比,全极化数据所包含的额外信息将大大提高雷达识别非合作目标的可能性。
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Decomposition of the radar target scattering matrix with application to high resolution target imaging
The basic theory of polarimetric radar and various decomposition theories are briefly reviewed. A novel decomposition of the scattering matrix is then presented with special reference to high-resolution imaging. By decomposing the scattering matrix into three different components, it is possible to resolve different types of scatterers even if they are within the same resolution cell of the image. This allows for a better resolution of the target scattering properties as well as a better characterization of the type of scattering for the individual contributions. The usefulness of this decomposition and the advantage in general of utilizing full polarimetric data in connection with radar target imaging are demonstrated by applying the decomposition to simulated images of a complex target model composed of a number of individual scatterers. The extra information contained in the full polarimetric data as compared with single polarization data should greatly improve the possibility of noncooperative target recognition by radar.<>
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