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ISTIS Improves Surface Threat Detection

Customer U.S. Navy
Need As the type of threat that the US Navy faces evolves, the problem of identification has become more complex and severe. Rather than a military entity that tends to operate far from civilian traffic, the current threat tends to operate close to and hide within groups of civilian surface craft, even utilizing such craft themselves. In order to determine the most suspicious and threatening tracks, personnel require an intelligent examination of each track’s behavior and other information available. These highlighted tracks can then receive priority for the limited ID sensor resources.
Solution Stottler Henke has developed a software system, the Intelligent Surface Threat Identification System (ISTIS), based on Artificial Intelligence (AI) techniques that improves the surface threat ID process, quality, and efficiency in the Littoral Combat Ship (LCS) and its Surface Mission Module. This improved performance includes better use of scarce ID resources, better ID estimations from available information, sooner ID determinations, ID accomplished at a greater range, prevention of ID “surprises,” and successful operation in more complex environments. ISTIS automatically analyzes the data associated with a track, hypothesizes, draws inferences, and makes ID-related recommendations. These data include the track’s location and/or velocity reported over time and other ID related reports such as IFF codes, visual ID reports, etc. ISTIS demonstrates a significant potential for improved ID performance and reduced LCS ID manning. Other LCS applications and other ship types could also benefit from these techniques.
Capabilities
  • Track Merge-Split and Fade/Reappear Processing using Multiple Hypotheses Reasoning to prevent ID swap and engage in process of elimination reasoning.
  • Maneuver Correlation Detection to ID tracks maintaining an intercept course, working cooperatively, avoiding an intercept, etc.
  • Behavior Analysis and Surface ID Data Fusion and Processing to automatically determine the likely platform type, its affiliation and intentions, and associate certainty.
  • Action Recommendations based on Heuristics for ownship, UAV, and helicopter maneuvers and actions.
  • Route Planning to identify a set of contacts and/or search an area.
  • Ability of tactical personnel to edit and change ID, alerting, and recommendation behaviors.
  • Provide identification and notification of threat behavior from both current and historical track analysis for one to all tracks observed.
  • Integrated and tested in the Lockheed Martin Technology Collaboration Center (TCC) simulated LCS environment with variable radar/sensor input.