Synthetic data accuracy sensitivity to CAD model accuracy using ATR-based metrics

Elizabeth R. Sudkamp; John W. Nehrbass; Eric Branch; Michael Levy

doi:10.1117/12.2523456

14 May 2019 Synthetic data accuracy sensitivity to CAD model accuracy using ATR-based metrics

Elizabeth R. Sudkamp, John W. Nehrbass, Eric Branch, Michael Levy

Proceedings Volume 10987, Algorithms for Synthetic Aperture Radar Imagery XXVI; 109870I (2019) https://doi.org/10.1117/12.2523456
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

In this paper we present a methodology for validating a 3D Computer Aided Design (CAD) model's accuracy for radar data synthesis. CAD models have been used to generate computer simulated radar frequency (RF) data. One problem with existing CAD-based simulations is that there is no metric or tool to verify whether data produced from the CAD model can be classified correctly before and after modifications have been made. This paper presents a methodology to quantify the similarities and differences in data generated from CAD models before and after modifications and presents this information through confusion matrices and a visualization technique. Results for three experiments involving CAD model modifications are presented.

Conference Presentation

Citation Download Citation

Elizabeth R. Sudkamp, John W. Nehrbass, Eric Branch, and Michael Levy "Synthetic data accuracy sensitivity to CAD model accuracy using ATR-based metrics", Proc. SPIE 10987, Algorithms for Synthetic Aperture Radar Imagery XXVI, 109870I (14 May 2019); https://doi.org/10.1117/12.2523456

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