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首页> 外文期刊>Journal of Sensors >Modified Hybrid Freeman/Eigenvalue Decomposition for Polarimetric SAR Data
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Modified Hybrid Freeman/Eigenvalue Decomposition for Polarimetric SAR Data

机译:极化SAR数据的修正混合Freeman /特征值分解

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摘要

Because of the rapid advancement of the airborne sensors and spaceborne sensors, large volumes of fully polarimetric synthetic aperture radar (PolSAR) data are available, but they are too complex to interpret difficultly. In this paper, a modified hybrid Freeman/eigenvalue decomposition method for the coherency matrix derived from the fully PolSAR sensors is proposed. The proposed modified hybrid Freeman/eigenvalue decomposition uses a real unitary transformation on the coherency matrix to release correlations between the copolarized term and cross polarized term, and the scattering models are derived from eigenvectors of the coherency matrix with reflection symmetry condition. The anisotropy and entropy are used to determine whether the volume scattering component is derived from the man-made structures or not. Moreover, the scattering powers from the proposed hybrid Freeman/eigenvalue decomposition are all nonnegative values. Fully PolSAR data on San Francisco acquired by AIRSAR sensor are used in the experiments to prove the efficacy of the proposed decomposition.
机译:由于机载传感器和星载传感器的飞速发展,可获得大量的全极化合成孔径雷达(PolSAR)数据,但它们太复杂而难以解释。本文提出了一种改进的混合Freeman /特征值分解方法,用于从完全PolSAR传感器导出的相干矩阵。所提出的改进的混合Freeman /特征值分解对相干矩阵使用了实ary变换来释放同极化项和交叉极化项之间的相关性,并且散射模型是从具有反射对称条件的相干矩阵的特征向量导出的。各向异性和熵用于确定体积散射分量是否来自人造结构。此外,所提出的混合Freeman /特征值分解的散射能力均为非负值。实验中使用了AIRSAR传感器获取的旧金山的完全PolSAR数据,以证明所提出的分解的有效性。

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