SAR detection and recognition filters

David P. Casasent; Satoshi Ashizawa

doi:10.1117/12.281550

28 July 1997 SAR detection and recognition filters

David P. Casasent, Satoshi Ashizawa

Proceedings Volume 3070, Algorithms for Synthetic Aperture Radar Imagery IV; (1997) https://doi.org/10.1117/12.281550
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

New variations of MINACE filters are considered for detection and recognition of objects and rejection of clutter in synthetic aperture radar (SAR) data. Multiple classes of objects with distortions present must be handled. Good performance in the presence of object obscurations is also needed. We present initial very attractive results that aid different modules in a SAR automatic target recognition processor. For 4 class test set data, we show detection performance of P_D > 99.8 percent with P_FA is congruent to 0.026/km²; for classification we show P_C > 96.6 percent with P_FA is congruent to 0.026/km². Selected tests with noise and obscurations present and of object in real SAR background are also included. All results used full shift-invariance tests.

Citation Download Citation

David P. Casasent and Satoshi Ashizawa "SAR detection and recognition filters", Proc. SPIE 3070, Algorithms for Synthetic Aperture Radar Imagery IV, (28 July 1997); https://doi.org/10.1117/12.281550

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