TRACking Expert (TRACE)

Rise in air traffic is introducing more challenges in target tracking, and current solutions are simply not scalable enough to meet these challenges. Better tracking capabilities are needed to keep up with present demands and to stay ahead of future ones as they grow in both amount and sophistication. This can be accomplished by making better use of space-based assets, specifically proliferated LEO constellations of satellites. LEO satellites are small and relatively inexpensive, making them ideal for creating dense constellations that can provide significant coverage across space. In order to realize the full benefit of proliferated LEO constellations on the problem of target tracking, we need distributed, satellite-based software that performs the tracking autonomously at orbital speeds and with limited communication. Stottler Henke proposes to develop TRACE, an AI expert system that would leverage our past work and customize it for the problem of automated target track management in conjunction with autonomous tip & cue by proliferated LEO constellations.  The intention is for TRACE to take in data observed by itself and other satellites, generate tasks for searching/detecting, tracking, and identification, and then schedule the generated tasks in the most optimal way possible by integrating our scheduling technology and expertise.