Analysis of spatially mismatched imagery for synthetic aperture radar ATR classification

Chad T. Rupp; Shawn D. Halversen; Lee J. Montagnino; Christina L. Hebert; Matthew T. Young; Mary L. Cassabaum; Neilson Ku

doi:10.1117/12.778105

2 May 2008 Analysis of spatially mismatched imagery for synthetic aperture radar ATR classification

Chad T. Rupp, Shawn D. Halversen, Lee J. Montagnino, Christina L. Hebert, Matthew T. Young, Mary L. Cassabaum, Neilson Ku

Author Affiliations +

Proceedings Volume 6967, Automatic Target Recognition XVIII; 69670H (2008) https://doi.org/10.1117/12.778105
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Template-based classification algorithms used with synthetic aperture radar (SAR) automatic target recognition (ATR) degrade in performance when used with spatially mismatched imagery. The degradation, caused by a spatial mismatch between the template and image, is analyzed to show acceptable tolerances for SAR systems. The mismatch between the image and template is achieved by resampling the test imagery to different pixel spacings. A consistent SAR dataset is used to examine pixel spacings between 0.1069 and 0.2539 meters with a nominal spacing of 0.2021 meters. Performance degradation is observed as the pixel spacing is adjusted, Small amounts of variation in the pixel spacing cause little change in performance and allow design engineers to set reliable tolerances. Alternatively, the results show that using templates and images collected from slightly different sensor platforms is a very real possibility with the ability to predict the classification performance.

Citation Download Citation

Chad T. Rupp, Shawn D. Halversen, Lee J. Montagnino, Christina L. Hebert, Matthew T. Young, Mary L. Cassabaum, and Neilson Ku "Analysis of spatially mismatched imagery for synthetic aperture radar ATR classification", Proc. SPIE 6967, Automatic Target Recognition XVIII, 69670H (2 May 2008); https://doi.org/10.1117/12.778105

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