Cognitive Radar for Classification

The article presents the cognitive radar architecture of Fraunhofer FHR based on a three-layer model of human cognitive performance. The approach is illustrated using examples for non-cooperative target identification and classification. On the skill based layer, a target-matched waveform design is presented and experimental results are shown. For the transition to the rule-based layer, convolutional neural networks are explained for the identification of air-targets and a novel auto-encoder for change detection is introduced. For rule-based behavior, a policy based decision making algorithm for NCTI waveform selection is explained, using CPOMDPs.