Surface Ship Surveillance from Space Based Radar

Not Available AI and Expert System technology offer the capability of capturing human decision processes. Developing a general schema for capturing the knowledge required for each CIC position facilitates the development of Intelligent Watch Station Software Modules to automatically perform the associated watch station's tasks, including filtering, collecting, correlating, interpreting, identifying, processing, evaluating, and fusing the data from the sensor systems while controlling, monitoring, adjusting, configuring and optimizing their equipment. These software modules represent a layer of intelligence between the tactical decision makers and the equipment. But the representation and automatic execution of CIC knowledge is a complex problem. What is needed is an integrated approach using a broad range of technologies. We will develop a general schema for CIC knowledge representation using AI techniques such as task transition diagrams, knowledge-based representations (rules, objects), case-based reasoning, intelligent entities, tactical diagrams, constraint-satisfaction, and fuzzy logic. The primary goal is to support a radically reduced manning concept in the CIC. In Phase I, we will design an intelligent CIC watch station automation system which includes a general CIC knowledge representation schema, investigate the knowledge required for several watch stations, implement a limited prototype CIC knowledge representation and execution system, and implement three limited automated watch station prototypes for different CIC positions using the schema