合成孔径雷达
旋光法
计算机科学
矩阵分解
分解
算法
雷达成像
无损压缩
遥感
雷达
模式识别(心理学)
散射
人工智能
数据压缩
特征向量
物理
光学
生物
电信
量子力学
地质学
生态学
作者
Bin Zou,Da Lu,Lamei Zhang,Wooil M. Moon
标识
DOI:10.1109/tgrs.2017.2670261
摘要
Polarimetric target decomposition is the most commonly used method of extracting information from polarimetric synthetic aperture radar (SAR) images. Coherent target decomposition methods are usually suitable for high-resolution images. Recently, Paladini reviewed coherent target decomposition methods and proposed a new approach, lossless and sufficient target decomposition (LSTD), using the special unitary matrix SU(4). However, this method suffers from parameter dependence and commutation problems that could introduce errors in parameter estimation such as an erroneous odd-even bounce ratio. In order to overcome these problems, a new model to decompose the circular polarization scattering vector is proposed. In this paper, the model applies a mapping from SU(4) to SU(6) to simplify the target representation while meaningful parameters, which are independent, can be extracted. Fully polarimetric L-band UAVSAR data are used to validate the proposed method. The most important odd-even bounce ratio parameter is used to compare the estimation accuracy between the proposed method and LSTD. Results show that the proposed method can extract parameters more accurately.
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