A Unified Framework for General Compact and Quad Polarimetric SAR Data and Imagery Analysis

Dual and compact polarimetric (CP) synthetic aperture radar (SAR) provide more target information than single-polarization SAR systems with less stringent data requirements than fully polarimetric SAR systems. Considering the incomplete nature of CP data to establish the quad or fully polarimetric s...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on geoscience and remote sensing Vol. 52; no. 1; pp. 582 - 602
Main Authors Sabry, Ramin, Vachon, Paris W.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.01.2014
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Dual and compact polarimetric (CP) synthetic aperture radar (SAR) provide more target information than single-polarization SAR systems with less stringent data requirements than fully polarimetric SAR systems. Considering the incomplete nature of CP data to establish the quad or fully polarimetric scattering matrix, the applied CP mode determines the captured scattering properties. Present formalism enables investigation of various CP modes (e.g., general elliptical transmission) and products for general target backscattering characterization. This is done through decomposition of quad-pol covariance and CP modeling of respective basic scattering mechanisms. On this basis, derivation of optimal CP modes and design of suitable CP products are explored. In this approach, the need for a priori target assumptions is removed. The link established between general CP and quad polarimetric covariance matrices can be used to examine target property assumptions using various CP modes data. Accordingly, means is also provided to explore a priori target property assumptions and their suitability required for expansion of 2 \times 2 CP covariance matrix to perform the pseudo-quad-polarimetric covariance analysis.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2013.2242479