A Predictive Framework for Adversarial Energy Depletion in Inbound Threat Scenarios

Abstract

This paper presents a predictive framework for adversarial energy-depletion defense against a maneuverable inbound threat (IT). The IT solves a receding-horizon problem to minimize its own energy while reaching a high-value asset (HVA) and avoiding interceptors and static lethal zones modeled by Gaussian barriers. Expendable interceptors (EIs), coordinated by a central node (CN), maintain proximity to the HVA and patrol centers via radius-based tether costs, deny attack corridors by harassing and containing the IT, and commit to intercept only when a geometric feasibility test is confirmed. No explicit opponent-energy term is used, and the formulation is optimization-implementable. No simulations are included.