Target classification in synthetic aperture radar using map-seeking circuit technology

Cameron K. Peterson; Patricia Murphy; Pedro Rodriguez

doi:10.1117/12.884015

4 May 2011 Target classification in synthetic aperture radar using map-seeking circuit technology

Cameron K. Peterson, Patricia Murphy, Pedro Rodriguez

Proceedings Volume 8051, Algorithms for Synthetic Aperture Radar Imagery XVIII; 805113 (2011) https://doi.org/10.1117/12.884015
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Conventional target recognition approaches for SAR include template matching and feature-based classification. However, unlike visual imagery, Synthetic Aperture Radar (SAR) presents a unique challenge in that many attributes, such as scattering centers, are extremely pose dependent and wink in and out with even minor viewing geometry changes. This work implements a highly efficient biologically-inspired 3D template-based approach, the Map Seeking Circuit (MSC) algorithm, for target recognition in SAR. Instead of exhaustively searching a high dimensional state space, the MSC algorithm efficiently searches a superposition hypersurface to estimate target location and 3D pose. Results are shown from applying the algorithm to real SAR datasets.

Citation Download Citation

Cameron K. Peterson, Patricia Murphy, and Pedro Rodriguez "Target classification in synthetic aperture radar using map-seeking circuit technology", Proc. SPIE 8051, Algorithms for Synthetic Aperture Radar Imagery XVIII, 805113 (4 May 2011); https://doi.org/10.1117/12.884015

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