Probabilistic Game-theory Architecture for Counter Swarm Measures

Barron Associates proposes to develop the Probabilistically Optimal Counter Swarm (Pro-CS) system, which offers a holistic approach to the intent analysis and defeat of adversarial UAS swarms and integrates with the “Defeat” component of existing counter-UAS kill chains. Pro-CS consists of four primary systems that work together to determine the intent of adversarial swarms, compute an optimal strategic response, plan mission details for realizing that response, and deploy an autonomous counter-swarm executing that mission. The system is designed from the ground up to address the inherent asymmetry in swarm/counter-swarm engagements when defending a fixed installation. Its reasoning engine accommodates a wide variety of uncertainty sources that may complicate the process of defining the best course of action in any engagement, including unknown adversary intent and capabilities. Its probabilistic reasoning engine balances the attendant risks over the course of an engagement, adapting based on what can be inferred from the swarm’s actions. The design leverages Barron Associates’ long history of related R&D in automated behavioral analysis, probabilistic reasoning, swarm autonomy, and flight guidance, navigation, and control (GNC).