In this paper, target at sea detection is addressed using hybrid-polarity (HP) synthetic aperture radar (SAR) architecture. Wave polarimetry concepts are used to define HP features that are used to observe targets at sea. The sensitivity of HP features to both targets and the surrounding environment is analyzed through a novel objective norm, namely the Relative Sensitivity for Polarimetric Features (RSPolF) index. Detection performance is evaluated by the novel Dependency of Sea state and Target (DoST) surface characteristics metric, and by the well-known Figure of Merit (FoM). Experiments undertaken on HP measurements emulated from Radarsat-2 and ALOS-PALSAR full-polarimetric actual SAR data demonstrate the effectiveness of the proposed HP approach and the different sensitivity of HP features to targets and background sea characteristics. Following those results, a ranking of the HP features performance is proposed which mainly highlights that HP features complement each other in the detection process. Finally, a constant false alarm rate (CFAR) approach is proposed to exploit two HP features for target detection in an unsupervised way.

On the capability of hybrid-polarity features to observe metallic targets at sea

NUNZIATA, FERDINANDO;MIGLIACCIO, Maurizio
2016-01-01

Abstract

In this paper, target at sea detection is addressed using hybrid-polarity (HP) synthetic aperture radar (SAR) architecture. Wave polarimetry concepts are used to define HP features that are used to observe targets at sea. The sensitivity of HP features to both targets and the surrounding environment is analyzed through a novel objective norm, namely the Relative Sensitivity for Polarimetric Features (RSPolF) index. Detection performance is evaluated by the novel Dependency of Sea state and Target (DoST) surface characteristics metric, and by the well-known Figure of Merit (FoM). Experiments undertaken on HP measurements emulated from Radarsat-2 and ALOS-PALSAR full-polarimetric actual SAR data demonstrate the effectiveness of the proposed HP approach and the different sensitivity of HP features to targets and background sea characteristics. Following those results, a ranking of the HP features performance is proposed which mainly highlights that HP features complement each other in the detection process. Finally, a constant false alarm rate (CFAR) approach is proposed to exploit two HP features for target detection in an unsupervised way.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/52225
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