Applications of knowledge based systems to surveillance

Abstract

The use of artificial intelligence (AI) tools to enhance radar signal processing is discussed. Knowledge-based trackers, a knowledge-based target identification system, and an expert system for operating and controlling the modes and parameters of an advanced multifunction surveillance system are presented. In the case of the track detector, a low threshold criterion is set for the incoming signal, which consequently allows a high probability of false alarm. Through use of a knowledge base and constraints on the target dynamics, realistic trajectories are sorted out to establish a declaration/detection for a track. For identification, a variety of signal features depicting different targets are matched with features derived from the received signal. A target is identified when the received signal is found to contain that set of features which is unique to a feature set in the knowledge base. A radar operator expert system assesses radar scenario situations and responds by controlling the parameters, modes and resources to optimize the overall performance and mission.<>