论文标题
基于服务质量的雷达资源管理使用深入的强化学习
Quality of service based radar resource management using deep reinforcement learning
论文作者
论文摘要
智能雷达资源管理是开发认知雷达系统的重要里程碑。基于服务的资源分配模型（Q-RAM）是一个允许智能决策的框架，但经典解决方案似乎不足以在现代雷达系统中实时应用。在本文中，我们使用深度强化学习的运行时性能提高了Q-RAM雷达资源管理问题的解决方案。
An intelligent radar resource management is an essential milestone in the development of a cognitive radar system. The quality of service based resource allocation model (Q-RAM) is a framework allowing for intelligent decision making but classical solutions seem insufficient for real-time application in a modern radar system. In this paper, we present a solution for the Q-RAM radar resource management problem using deep reinforcement learning considerably improving on runtime performance.
