1 December 2002 Increasing the discrimination of synthetic aperture radar recognition models
Author Affiliations +
Optical Engineering, 41(12), (2002). doi:10.1117/1.1517286
The focus of this work is optimizing recognition models for synthetic aperture radar (SAR) signatures of vehicles to improve the performance of a recognition algorithm under the extended operating conditions of target articulation, occlusion, and configuration variants. The recognition models are based on quasi-invariant local features, scattering center locations, and magnitudes. The approach determines the similarities and differences among the various vehicle models. Methods to penalize similar features or reward dissimilar features are used to increase the distinguishability of the recognition model instances. Extensive experimental recognition results are presented in terms of confusion matrices and receiver operating characteristic (ROC) curves to show the improvements in recognition performance for real SAR signatures of vehicle targets with articulation, configuration variants, and occlusion.
Bir Bhanu, Grinnell Jones, "Increasing the discrimination of synthetic aperture radar recognition models," Optical Engineering 41(12), (1 December 2002). http://dx.doi.org/10.1117/1.1517286

Synthetic aperture radar


Data modeling

Detection and tracking algorithms

Performance modeling

Optical engineering

Systems modeling

Back to Top