Data Compression for Multilook Polarimetric SAR Data

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.