Artificial Intelligence Techniques for Surface Threat Identification

Stottler Henke proposes a software system, the Intelligent Surface Threat Identification System (ISTIS), based on Artificial Intelligence (AI) techniques and our previous work, an existing Navy ID system, the Intelligent Identification Software Module (IISM). ISTIS will automatically analyze the data associated with a track, hypothesize, draw inferences, and make ID related recommendations. These data include the tracks' location and/or velocity reported over time and other ID related reports such as IFF codes, visual ID reports, acoustic signature, specific emitter ID (SEI), ELINT signature, FLIR reports, intelligence reports, communications, etc. The ultimate goal of this proposed effort is to improve the quality and efficiency of the ID process. This improved performance includes better use of scarce ID resources, better ID estimations from available information, sooner ID determinations, prevention of ID "surprises", and operating successfully in more complex environments. The goals of the Phase I research are to understand the current and potential ID environment, especially in littoral areas of interest to the US Navy; elaborate the heuristics, algorithms and techniques for automatic ID analysis; prove the feasibility of the techniques through prototype development; and develop the Phase II system design.