Upgraded Planner for Defense of Guam (UPDOG)

Battlefield command and control (C2) has become increasingly complex as new threats arise and additional assets are fielded. This increased complexity has been observed recently in multiple conflicts, such as Ukraine, Israel, and the Red Sea, where combined assaults of drone swarms, cruise missiles, and ballistic missiles have been employed against a layered defense. While these conflicts demonstrate the challenge of defending against saturation raids employing mixed threats, they still represent a limited attack in comparison to the exercises being conducted by China around Taiwan which could be augmented with a simultaneous attack on Guam. Such an attack would surely employ longer range, more lethal and challenging threats launched from a combination of the continent, long range aviation, surface and subsurface vessels.To address this complexity, SciTec proposes to develop the Upgraded Planner for Defense of Guam (UPDOG) architecture as a series of C2 Agents providing course of action (COA) recommendation at both the individual sensor and shooter level (COA generation) and the GDS C2 systems level (COA decisions and subsequent sensor/shooter tasking). To train the C2 Agents, SciTec will employ our extensive modelling and simulation capabilities, combined with integrated GFx 3rd party models of various sensor and shooter elements, to parametrically create a large dataset of unique Defense of Guam raid scenarios to be defended against. These scenarios will leverage in-house and 3rd party threat generation software, including generation of threat trajectory, infrared boost and hardbody signature, and radar cross section values for accurate sensor measurements. Ultimately, we’ll benchmark our UPDOG MVP against one or more of the JRCIM scenarios, which are Defense of Guam raids crafted to challenge defensive capabilities.Once we demonstrate the value of the UPDOG MVP, we’ll be positioned to transition it to a more complete capability, ultimately increasing the characterization of the GDS C2 System Agents through further test on playback data and ultimately through experimentation on future live fire demonstrations that build upon the capabilities demonstrated in the recent Flight Experiment Mission-02 (FEM-02). Once matured and deployed with distributed access to all relevant data sources, future versions of UPDOG, acting as COA recommendation engines, will provide the necessary force multiplier to warfighters defending against the most complex, multi-domain raids envisioned.