Principles and evaluation of an automatic target recognition system for synthetic aperture radar imagery based on the use of functional templates

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Abstract
We describe an end-to-end Automatic Target Recognition (ATR) system for recognizing targets in Synthetic Aperture Radar (SAR) imagery. The system heavily relies on the use of functional template correlation, a technique recently developed by the authors for applying machine intelligence directly at the pixel level through the use of functional templates (FTs). Targets are detected using a CFAR-like, circularly-symmetric FT. They are recognized with azimuth-dependent FTs that deal with the fact that the appearance of an object in SAR imagery changes significantly with the direction of radar illumination relative to the object. FTs were specifically designed for ISAR data at 19 deg depression angle. Excellent recognition results were obtained when these FTs were blindly applied to over 20,000 ISAR images covering depression angles from 18 to 32 deg. When the same FTs were applied to 255 airborne stripmap SAR images at 22 deg, good recognition results were obtained with no false alarms. Although the paper deals primarily with fully polarimetric data, the ideas presented readily apply to single- or dual-polarization SARs.

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