TY - GEN
T1 - Unique decomposition of a POLSAR coherency matrix using a generalized scattering model
AU - Kusano, Shunichi
AU - Takahashi, Kazunori
AU - Sato, Motoyuki
PY - 2013/12/1
Y1 - 2013/12/1
N2 - We propose a new POLSAR model-based decomposition with a generalized scattering model. The generalized scattering model is built by adding the ellipticity angle with the particle cloud model. The model is flexible so that it represents surface scattering, double-bounce, volume scattering, and helix scattering. Moreover, a decomposition procedure to use the generalized model is proposed. First, the model parameters are determined so that the resultant model matrix can be subtracted from the observed coherency matrix as much as possible with keeping the residual matrix positive semidefinite. Next, the same operation is applied to the residual matrix with a new parameter set. By repeating this process, the residual matrix becomes null at last and the decomposed matrices perfectly fit the observed one. The decomposition results were compared to the results of the eigenvalue-based decomposition. Due to the orientation randomness, the proposed decomposition makes the interpretation straightforward and has a possibility of making the classification easy.
AB - We propose a new POLSAR model-based decomposition with a generalized scattering model. The generalized scattering model is built by adding the ellipticity angle with the particle cloud model. The model is flexible so that it represents surface scattering, double-bounce, volume scattering, and helix scattering. Moreover, a decomposition procedure to use the generalized model is proposed. First, the model parameters are determined so that the resultant model matrix can be subtracted from the observed coherency matrix as much as possible with keeping the residual matrix positive semidefinite. Next, the same operation is applied to the residual matrix with a new parameter set. By repeating this process, the residual matrix becomes null at last and the decomposed matrices perfectly fit the observed one. The decomposition results were compared to the results of the eigenvalue-based decomposition. Due to the orientation randomness, the proposed decomposition makes the interpretation straightforward and has a possibility of making the classification easy.
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M3 - Conference contribution
AN - SCOPUS:84894176949
SN - 9784885522789
T3 - Conference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013
SP - 559
EP - 560
BT - Conference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013
T2 - 2013 4th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013
Y2 - 23 September 2013 through 27 September 2013
ER -