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Decentralized algorithms for netcentric force protection against antiship missiles

机译:用于反舰导弹的网心力保护的分散算法

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摘要

We model a decentralized network of decision makers charged with optimally deploying hardkill and/or softkill weapons (countermeasures (CMs)) to defend a task group from antiship missiles. Each platform (decision maker) observes missile threats using a combination of shipboard sensor measurement data and data from other ships, but acts independently when controlling its own weapon systems to cooperatively pursue the defensive objectives of the task group in a decentralized fashion. The main results are a formulation of the missile deflection problem as a stochastic shortest path Markovian game with constraints, a characterization of the Nash equilibrium solution, and a decentralized algorithm for computing the Nash equilibrium when the stochastic game is collaborative. Numerical examples are given to demonstrate the equilibrium policies and illustrate their sensitivity to the missile dynamics.
机译:我们为决策者的分散网络建模,负责最佳部署硬杀伤性和/或软杀伤性武器(对策(CM)),以保护工作组免受反舰导弹的攻击。每个平台(决策者)都使用舰载传感器测量数据和其他船舶的数据来观察导弹威胁,但是在控制自己的武器系统以分散方式共同追求任务组的防御目标时会独立行动。主要结果是将导弹偏转问题表述为具有约束的随机最短路径马尔可夫博弈,纳什均衡解的特征,以及在协作的情况下用于计算纳什均衡的分散算法。数值例子说明了平衡策略,并说明了其对导弹动力学的敏感性。

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