Adaptive target recognition

Target recognition is a multi-level process requiring a sequence of algorithms at low, intermediate and high levels. Generally,such systems are open loop with no feedbackbetween levels and assuring their performance at the given Probability of Correct Identification (PCI) and ProbabilityofFalse Alarm (Pf)isakey challenge in computer vision and pattern recognition research. In this paper a robust closed-loop system for recognition of SAR images based on reinforcement learning is presented. The parameters in model-based SAR target recognition are learned. The method meets performance specifications byusingPCI and Pf as feedbackfor the learning system. It has been experimentally validated by learning the parameters of the recognition system for SAR imagery, successfully recognizing articulated targets, targets of different configuration and targets at different depression angles. Keywords: Target Recognition, Reinforcement Learning, Parameter Learning