This letter studies the conformity with the reciprocity theorem on the measured polarimetric synthetic aperture radar (SAR) data. The problem is formalized via a binary hypothesis test where the reciprocity assumption is tested versus its alternative (absence of reciprocity). The generalized likelihood ratio (GLR) is used as design criterion and the resulting decision rule ensures the constant false alarm rate (CFAR) property. At the analysis stage, the performance of the GLR statistic is analyzed on the simulated data as well as on two different measured data sets (collected by two systems) thus highlighting the effectiveness of the approach.

Aubry, A., Carotenuto, V., De Maio, A., Pallotta, L. (2020). Assessing Reciprocity in Polarimetric SAR Data. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 17(1), 87-91 [10.1109/LGRS.2019.2915119].

Assessing Reciprocity in Polarimetric SAR Data

Pallotta L.
2020-01-01

Abstract

This letter studies the conformity with the reciprocity theorem on the measured polarimetric synthetic aperture radar (SAR) data. The problem is formalized via a binary hypothesis test where the reciprocity assumption is tested versus its alternative (absence of reciprocity). The generalized likelihood ratio (GLR) is used as design criterion and the resulting decision rule ensures the constant false alarm rate (CFAR) property. At the analysis stage, the performance of the GLR statistic is analyzed on the simulated data as well as on two different measured data sets (collected by two systems) thus highlighting the effectiveness of the approach.
Aubry, A., Carotenuto, V., De Maio, A., Pallotta, L. (2020). Assessing Reciprocity in Polarimetric SAR Data. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 17(1), 87-91 [10.1109/LGRS.2019.2915119].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/362125
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