Performance characterization of a model-based SAR target recognition system using invariants

The performance of a model-based automatic target recognition (ATR) engine with articulated and occluded objects in Synthetic Aperture Radar (SAR) imagery is characterized based on invariant properties of the objects. Using SAR scattering center locations as features, the invariance with articulation (i.e. turret rotation for the T72, T80 and M1a1 tanks; missile erect vs. down for the SCUD launcher) is shown as a function of object azimuth. The basic elements of our model-based recognition engine are described and performance results are given for various design parameters. The articulation invariant properties of the objects are used to characterize recognition engine performance, in terms of probability of correct identification (PCI) as a function of percent invariance with articulation. Similar results are presented for object occlusion in the presence of noise? with percent unoccluded as the invariant measure. Finally, performance is characterized for occluded articulated objects as a function of number of features that are used. Results are presented using 4320 chips generated by XPATCH for 5 targets.