Visualisation and interpretation of PolSAR data based on polarimetric coherence

Abstract

Polarimetric coherence strongly relates to the target scattering characteristics. Coherences of different second-order statistics show different advantages in target discrimination in specific correspondence to physical scattering mechanism. A fast visualisation scheme of the coherency matrix and circular polarisation covariance matrix is developed by adopting the polarimetric coherence for the interpretation of polarimetric synthetic aperture radar (PolSAR) data. The scheme has much less computational burden compared with other decomposition and classification algorithms. It can be regarded as a basic operation of PolSAR data as the Pauli decomposition. Its strong relationship with polarimetric scattering entropy is revealed which substantiates the efficacy in terrain classification. The performance and advantages of the scheme are demonstrated on airborne synthetic aperture radar (AIRSAR) and Electromagnetics Institute synthetic aperture radar (EMISAR) datasets.

Keywords

• radar polarimetry
• synthetic aperture radar
• data visualisation
• statistical analysis
• matrix algebra
• physical scattering mechanism
• fast visualisation scheme
• circular polarisation covariance matrix
• polarimetric synthetic aperture radar data
• polarimetric scattering entropy
• target scattering characteristics
• polarimetric coherency matrix
• polsar data visualisation
• second-order statistics
• pauli decomposition
• terrain classification algorithms
• emisar datasets
• airsar datasets