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.

中文翻译：

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多体资产保护博弈中协作代理的优化分配

我们研究了导弹防御中的多体资产保护游戏，其中拦截导弹团队合作保护非机动资产，抵御一组威胁导弹。我们分两步解决这个问题。我们首先制定了一个分配问题，我们将协作拦截器的子集最优分配给每个威胁，以便所有威胁都在尽可能远离资产的地方被拦截。我们假设每个拦截器都由源自线性二次动态博弈的协同制导法则控制。我们的结果包括 5 个拦截器与 3 个威胁导弹交战的 6 自由度模拟，其中每个代理都被建模为由自动驾驶仪控制的导弹机身。尽管在我们的协同制导法则中假设了线性动力学以及模拟环境中的未建模动力学（例如，不同的密度和重力），我们表明模拟的轨迹与我们的方法预测的轨迹匹配得很好。此外，我们表明，当它们合作时，劣等拦截器可以拦截具有更高速度和加速度的更敏捷的威胁。我们相信本文介绍的概念可以应用于非对称导弹防御场景，包括防御先进巡航导弹和高超音速飞行器。