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Article Dans Une Revue IEEE Transactions on Geoscience and Remote Sensing Année : 2022

Bistatic Analysis Using the Real Representation Scattering Matrix Eigen-Classification

Résumé

Exploring polarimetric diversity of synthetic aperture radar (SAR) data is directly applicable to conventional monostatic cases. For this, the most used convention is the backscatter alignment. While establishing important advantages for the monostatic case (possibility to have equal values on the cross-polarimetric channels), it has been proven to introduce some difficulties for the bistatic case. This appears in relation to the so-called conjugate similarity operation, when (mathematically) asymmetric scattering matrices occur. In this article, we propose the detailed algorithm which provides a solution to the conjugate similarity operation, in the case of general scattering matrices. The proposed algorithm is based on the real representation (RR) matrix transformation. Furthermore, we investigate the characterization of canonical bistatic scatterers (three elementary targets). Raw bistatic polarimetric signals are obtained using simulations with a computationally electromagnetic (EM) software, capable of complete EM analysis. The eigenvalue classification illustrates the potential of additional information brought using the proposed RR scattering matrix (RRSM). The presence of complex eigenvalues is investigated in relation to the bistatic angle and one nonreciprocity parameter.
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Dates et versions

hal-03727546 , version 1 (21-07-2022)

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Madalina Ciuca, Gabriel Vasile, Andrei Anghel, Michel Gay, Silviu Ciochina. Bistatic Analysis Using the Real Representation Scattering Matrix Eigen-Classification. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60, pp.5228318. ⟨10.1109/TGRS.2022.3175475⟩. ⟨hal-03727546⟩
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