Neural processing of SAR imagery for enhanced target detection

Allen M. Waxman; Carol H. Lazott; David A. Fay; Alan N. Gove; W. R. Steele

doi:10.1117/12.210839

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5 June 1995 Neural processing of SAR imagery for enhanced target detection

Allen M. Waxman, Carol H. Lazott, David A. Fay, Alan N. Gove, W. R. Steele

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Proceedings Volume 2487, Algorithms for Synthetic Aperture Radar Imagery II; (1995) https://doi.org/10.1117/12.210839
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

Neural network models of early visual computation have been adapted for processing single polarization (VV channel) SAR imagery, in order to assess their potential for enhanced target detection. In particular, nonlinear center-surround shunting networks and multi-resolution boundary contour/feature contour system processing has been applied to a spotlight sequence of tactical targets imaged by the Lincoln ADT sensor at 1 ft resolution. We show how neural processing can modify the target and clutter statistics, thereby separating the poplulations more effectively. ROC performance curves indicating detection versus false alarm rate are presented, clearly showing the potential benefits of neural pre-processing of SAR imagery.

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Allen M. Waxman, Carol H. Lazott, David A. Fay, Alan N. Gove, and W. R. Steele "Neural processing of SAR imagery for enhanced target detection", Proc. SPIE 2487, Algorithms for Synthetic Aperture Radar Imagery II, (5 June 1995); https://doi.org/10.1117/12.210839

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