Hierarchical integration of sensor data and contextual information for automatic target recognition

摘要

Real-time assessment of high-value targets is an ongoing challenge for the defense community. Many automatic target recognition (ATR) approaches exist, each with specific advantages and limitations. An ATR system is presented here that integrates machine learning, expert systems, and other advanced image understanding concepts. The ATR system employs a hierarchical strategy relying primarily on abductive polynomial networks at each level of recognition. Advanced feature extraction algorithms are used at each level for pixel characterization and target description. Polynomial networks process feature data and situational information, providing input for subsequent levels of processing. An expert system coordinates individual recognition modules.