Our adversaries have evolved beyond conventional ballistic missile systems to developing and deploying advanced systems that travel long ranges at hypersonic velocities with the capability to maneuver to avoid detection from terrestrial-based sensor systems. These advanced threats were developed specifically to counter terrestrial sensors, making birth-to-death tracking extremely difficult due to limitations of available operational locations creating known coverage gaps. These coverage gaps can be exploited by hypersonic, maneuvering threat targets. The sensor track coverage problem can be addressed with space-based sensors. Given enough space vehicles with tracking sensors, birth-to-death tracking is feasible. However, there are technical challenges to achieve the required performance. One of the more difficult challenges is accurately tracking and classifying multiple closely spaced targets in a complex environment. Emerging signal chain processing algorithms will support meeting mission and system performance requirements. The algorithms will enable recognizing and discriminating fast moving, maneuverable targets from decoys and clutter in complex scenes that overhead persistent infrared (OPIR) sensors capture from space. ExoAnalytic Solutions, along with L3Harris, propose to demonstrate low-latency acquisition and tracking of highly maneuverable targets in complex environments. Our robust modeling and simulation framework, along with algorithms previously developed under HBTSS and other space and missile defense programs, provides the basis for design of an open framework algorithm architecture in which algorithms for target recognition, acquisition, and tracking will be tested.
