展开式薄膜遮光罩设计及重复展开精度研究

针对星敏感器的杂光抑制需求，设计了一种可以实现轴向展开的圆柱状展开式薄膜遮光罩，包括充气支撑管、薄膜蒙皮和挡光环，并完成了各构件的结构和材料设计。建立了薄膜蒙皮的运动学模型，分析了构型随着二面角的变化情况，验证了薄膜蒙皮采用hexagonal折纸样式可以完全折叠和展开。通过试验研究了遮光罩的重复展开精度，包括轴向和径向展开精度等。研制了遮光罩原理样机，并开展了地面展开试验，表明在充气支撑管的驱动下能够顺利展开，为大尺寸遮光罩的工程应用提供了新的技术方案。     

Reinforcement learning based dynamic distributed routing scheme for mega LEO satellite networks

Recently, mega Low Earth Orbit (LEO) Satellite Network (LSN) systems have gained more and more attention due to low latency, broadband communications and global coverage for ground users. One of the primary challenges for LSN systems with inter-satellite links is the routing strategy calculation and maintenance, due to LSN constellation scale and dynamic network topology feature. In order to seek an efficient routing strategy, a Q-learning-based dynamic distributed Routing scheme for LSNs (QRLSN) is proposed in this paper. To achieve low end-to-end delay and low network traffic overhead load in LSNs, QRLSN adopts a multi-objective optimization method to find the optimal next hop for forwarding data packets. Experimental results demonstrate that the proposed scheme can effectively discover the initial routing strategy and provide long-term Quality of Service (QoS) optimization during the routing maintenance process. In addition, comparison results demonstrate that QRLSN is superior to the virtual-topology-based shortest path routing algorithm.