Polarmetric classification of scattering centers

Emre Ertin; Lee C. Potter

doi:10.1117/12.242049

10 June 1996 Polarmetric classification of scattering centers

Emre Ertin, Lee C. Potter

Proceedings Volume 2757, Algorithms for Synthetic Aperture Radar Imagery III; (1996) https://doi.org/10.1117/12.242049
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

Polarimetric diversity can be exploited in synthetic aperture radar (SAR) for enhanced target detection and target description. Detection statistics and target features can be computed from either polarimetric imagery or parametric processing of SAR phase histories. We adopt an M- ary Bayes classification approach and derive Bayes-optimal decision rules for detection and description of scattering centers. Scattering centers are modeled as one of M canonical geometric types with unknown amplitude, phase and orientation angle; clutter is modeled as one of M canonical geometric types with unknown amplitude, phase and orientation angel; clutter is modeled as a spherically invariant random vector. For the Bayes optimal decision rules, we provide a simple geometric interpretation and an efficient computational implementation. Moreover, we characterize the certainty of decisions by deriving an approximate posteriori probability.

Citation Download Citation

Emre Ertin and Lee C. Potter "Polarmetric classification of scattering centers", Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); https://doi.org/10.1117/12.242049

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