Salvo Management Using Artificial Intelligence

System-wide battle management handles tasking and assignments to sensors and weapon systems, each weapon system then assigns weapons from its inventory and requests tasking. Mixed field inventory assignment and management can be difficult to optimize in light of fundamental uncertainties. Not only does salvo composition need to be constructed from more than one weapon system, but significant differences in ability and reliability of the various interceptors must also be considered. Additionally, salvo timing and management after launch in light of potential battle space updates should inform the battle management. Using threat state from the centralized battle manager, and considerations concerning the type of threat system being engaged in terms of fundamental capabilities – matching interceptor capabilities to threat capabilities provides technical merit. Considering fixed inventory sizes, and uncertain threat inventories, we define how highly capable and reliable weapons should be partitioned to address the threat. Salvo composition, timing and management, before as well as after launch is optimized with respect to available, and dynamic, threat information. We propose a solution that optimizes pre- and post-launch dynamic salvo assignment and re-assignment of mixed field inventory with innovative Artificial Intelligence that manages inventory across the battled and achieved required Pkill against diverse raid threats in the presence of multiple uncertainties. Approved for Public Release | 21-MDA-11013 (19 Nov 21)