Four-component scattering model for polarimetric SAR image decomposition
Four-component scattering model for polarimetric SAR image decomposition
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DOI：
10.1109/tgrs.2005.852084
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发表时间：
2005-08-01
影响因子：
8.2
通讯作者：
Yamada, H
中科院分区：
文献类型：
--
作者：
Yamaguchi, Y;Moriyama, T;Yamada, H
提出了一种四分量散射模型来分解极化合成孔径雷达（SAR）图像。采用协方差矩阵法处理无反射对称散射问题。该方案包含并扩展了Freeman和Durden提出的三分量分解方法，该方法处理同极和互极相关性接近于零的反射对称条件。受阻散射功率作为第四分量添加到描述表面、双反弹和体积散射的三分量散射模型。这个螺旋散射项被添加到考虑到共极化和交叉极化的相关性，通常出现在复杂的城市区域散射和消失的自然分布的散射体。这个术语与描述城市区域散射中的人造目标有关。此外，不对称的体积散射协方差矩阵的HH和W之间的相对后向散射幅度的依赖。偶极子散射体云的概率密度函数的一个修改产生不对称的协方差矩阵。在对称或非对称体积散射协方差矩阵中的适当选择使我们能够对测量数据进行最佳拟合。针对一般散射问题，提出了一种四分量分解算法。这种分解的结果表明，与L波段的Pi-SAR图像在日本的新泻市。
A four-component scattering model is proposed to decompose polaximetric synthetic aperture radar (SAR) images. The covariance matrix approach is used to deal with the non-reflection symmetric scattering case. This scheme includes and extends the three-component decomposition method introduced by Freeman and Durden dealing with the reflection symmetry condition that the co-pol and the cross-pol correlations are close to zero. Helix scattering power is added as the fourth component to the three-component scattering model which describes surface, double bounce, and volume scattering. This helix scattering term is added to take account of the co-pol and the cross-pol correlations which generally appear in complex urban area scatttering and disappear for a natural distributed scatterer. This term is relevant for describing man-made targets in urban area scattering. In addition, asymmetric volume scattering covariance matrices are introduced in dependence of the relative backscattering magnitude between HH and W. A modification of probability density function for a cloud of dipole scatterers yields asymmetric covariance matrices. An appropriate choice among the symmetric or asymmetric volume scattering covariance matrices allows us to make a best fit to the measured data. A four-component decomposition algorithm is developed to deal with a general scattering case. The result of this decomposition is demonstrated with L-band Pi-SAR images taken over the city of Niigata, Japan.