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Data Compression for Multilook Polarimetric SAR Data

机译:多视极化SAR数据的数据压缩

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This letter attempts to address the problem on the emergence of negative eigenvalues in the coherency matrix after the compressing of multilook polarimetric synthetic aperture radar (SAR) data. A new nine-parameter expression for the eigenvalue decomposition of the coherency matrix is introduced, and a new compression algorithm is proposed for multilook polarimetric data with this expression. By comparing it with the NASA/Jet Propulsion Laboratory's Airborne SAR compression algorithm, the authors analyze the new algorithm's compression accuracy, signal-to-noise ratio, and the ability to preserve the data's polarimetric property. For polarimetric SAR data, it is important to preserve the polarimetric property of a target. The proposed algorithm has this ability which is illustrated by the comparison of the polarimetric signatures. Finally, the effectiveness of the proposed methods is demonstrated by using the experimental SAR data.
机译:这封信试图解决在压缩多视极化合成孔径雷达(SAR)数据后,相干矩阵中出现负特征值的问题。引入了一种新的用于相干矩阵特征值分解的九参数表达式,并针对具有该表达式的多视偏振数据提出了一种新的压缩算法。通过将其与NASA /喷气推进实验室的机载SAR压缩算法进行比较,作者分析了新算法的压缩精度,信噪比以及保留数据极化特性的能力。对于极化SAR数据,重要的是保留目标的极化特性。所提出的算法具有这种能力,这可以通过极化特征的比较来说明。最后,通过实验SAR数据证明了所提方法的有效性。

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