Optimal assignment of collaborating agents in multi-body asset-guarding games

TL;DR

This paper presents an optimal assignment strategy for collaborating interceptors in missile defense, demonstrating effective threat interception through simulation despite simplified dynamics and unmodeled environmental factors.

Contribution

It introduces a novel assignment approach combined with collaborative guidance laws for interceptors, validated through high-fidelity simulations.

Findings

Collaborative assignment improves interception success.

Simulated trajectories align with theoretical predictions.

Collaboration enables weaker interceptors to counter more agile threats.

Abstract

We study a multi-body asset-guarding game in missile defense where teams of interceptor missiles collaborate to defend a non-manuevering asset against a group of threat missiles. We approach the problem in two steps. We first formulate an assignment problem where we optimally assign subsets of collaborating interceptors to each threat so that all threats are intercepted as far away from the asset as possible. We assume that each interceptor is controlled by a collaborative guidance law derived from linear quadratic dynamic games. Our results include a 6-DOF simulation of a 5-interceptor versus 3-threat missile engagement where each agent is modeled as a missile airframe controlled by an autopilot. Despite the assumption of linear dynamics in our collaborative guidance law and the unmodeled dynamics in the simulation environment (e.g., varying density and gravity), we show that the simulated trajectories match well with those predicted by our approach. Furthermore, we show that a more agile threat, with greater speed and acceleration, can be intercepted by inferior interceptors when they collaborate. We believe the concepts introduced in this paper may be applied in asymmetric missile defense scenarios, including defense against advanced cruise missiles and hypersonic vehicles.