Simultaneous multitarget detection and false alarm mitigation algorithm for the Predator UAV TESAR ATR system

This paper describes a technique recently developed for target detection and false alarm reduction for the Predator unmanned aerial vehicle (UAV) tactical endurance synthetic aperture radar (TESAR) automatic target recognition (ATR) system. The approach does not attempt to label various objects in the SAR image (e.g., buildings, trees, roads); instead, it finds target-like characteristics in the image and compares their statistical/spatial relationship to larger structures in the scene. To do this, the approach merges the output of multiple CFAR (constant false alarm ratio) surfaces through a sequence of mathematical morphology tests. Application of this detector to the Predator´s SAR ATR algorithm suite produced a stunning reduction of 1 order of magnitude in the number of cues yielded by Predator´s baseline detector