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TitleA unified model for decomposition of coherent and partially coherent target scattering using polarimetric SARs
LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorTouzi, R
SourceIGARSS 2005: proceedings; vol. 7, 2005 p. 4844-4847
Alt SeriesEarth Sciences Sector, Contribution Series 2005133
PublisherInstitute of Electrical and Electronics Engineers, Inc. (Piscataway, NJ, USA)
MeetingIGARSS 2005 - IEEE International Geoscience and Remote Sensing Symposium; Seoul; KR; July 25-29, 2005
Mediapaper; on-line; digital
File formatpdf
Subjectsremote sensing; models; statistical methods; Data processing
Illustrationsremote sensing images; graphs
ProgramGeomatics for Sustainable Development of Natural Resources
Released2005 01 01
AbstractThe target scattering vector model (TSVM) introduced in [1] is reconsidered for a unified decomposition of coherent and partially coherent target scattering. The model, which is robust under change of antenna polarization basis, permits a unique representation of target coherent scattering in term of five parameters that are target characteristics. The TSVM is integrated in Cloude's incoherent decomposition method (ICTD) to derive the TSVM-ICTD, which permits a unique and basis invariant decomposition of natural extended target scattering. It is shown that both phase and magnitude of the complex scattering type should be used for an unambiguous description of symmetric scattering type.
The use of the TSVM helicity angle is important for the characterization of the symmetric nature of target scattering. This parameter permits solving for certain scattering type ambiguities that might occur with Cloude parameter with targets of non-symmetric scattering. Speckle effect on the TSVM parameter estimation is also discussed. It is shown that the TSVM parameters, and in particular the symmetric scattering type, can be significantly biased. The statistics of the coherence are used to determine the minimum window size required for an unbiased estimation of the TSVM decomposition parameters.

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