Polarimetric Autocorrelation Matrix: A New Tool for Joint Characterizing of Target Polarization and Doppler Scattering Mechanism

This paper introduces an innovative approach in Synthetic Aperture Radar (SAR) polarimetry and proposes a novel descriptor called polarimetric autocorrelation matrix. Different from polarimetric covariance and coherency matrices, the polarimetric autocorrelation matrix can capture hidden Doppler information in the frequency domain and encode it in the phase using higher-order statistical methods. This matrix facilitates the joint extraction and analysis of polarization and Doppler information from fully Polarimetric SAR (PolSAR) data through matrix analysis. The paper explains that the polarimetric autocorrelation matrix can be decomposed into a Doppler-related matrix and a covariance-related matrix. The magnitudes and phases of these matrices provide insight into Doppler shifts between different polarizations and the variance of the backscattering coefficient. Our research demonstrates how the Doppler shift is influenced not only by the target's radial velocity but also by radar polarization. Four quad-polarimetric RADARSAT-2 images are used for testing in this study, and a set of characterization features and parameters are derived from the polarimetric autocorrelation matrix. The novel descriptor, together with the new parameters, can detect man-made target and sea ice, mitigate ambiguity caused by moving targets, and indicate the motion status of ship targets and sea currents. Specifically for marine scenes, our data found Doppler differences in HH polarization and VV polarization induced by sea surface motion can be up to 100 Hz.