In this letter, an automatic method to validate the reciprocity theorem on full-polarimetric heterogeneous synthetic aperture radar (SAR) data is derived. The study extends, to the more general heterogeneous scenario, the work of [1], where the conformity with the reciprocity is studied in the homogeneous case. At the design stage, it is assumed that the pixels in the polarimetric image share the same covariance structure but different power levels. Then, the dependence on nuisance parameters is removed resorting to the Principle of Invariance. The resulting problem is formalized as a binary hypothesis test and is solved through the generalized likelihood ratio test (GLRT). Tests are conducted both on simulated and real-recorded data to show the superiority of the proposed GLRT with respect to its homogeneous counterpart.

Pallotta, L. (2022). Reciprocity Evaluation in Heterogeneous Polarimetric SAR Images. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 19, 1-5 [10.1109/LGRS.2020.3017518].

Reciprocity Evaluation in Heterogeneous Polarimetric SAR Images

Pallotta L.
2022-01-01

Abstract

In this letter, an automatic method to validate the reciprocity theorem on full-polarimetric heterogeneous synthetic aperture radar (SAR) data is derived. The study extends, to the more general heterogeneous scenario, the work of [1], where the conformity with the reciprocity is studied in the homogeneous case. At the design stage, it is assumed that the pixels in the polarimetric image share the same covariance structure but different power levels. Then, the dependence on nuisance parameters is removed resorting to the Principle of Invariance. The resulting problem is formalized as a binary hypothesis test and is solved through the generalized likelihood ratio test (GLRT). Tests are conducted both on simulated and real-recorded data to show the superiority of the proposed GLRT with respect to its homogeneous counterpart.
2022
Pallotta, L. (2022). Reciprocity Evaluation in Heterogeneous Polarimetric SAR Images. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 19, 1-5 [10.1109/LGRS.2020.3017518].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/396463
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