Review of sensor tasking methods in Space Situational Awareness
To ensure the secure operation of space assets, it is crucial to employ ground and/or space-
based surveillance sensors to observe a diverse array of anthropogenic space objects …
based surveillance sensors to observe a diverse array of anthropogenic space objects …
Optimal tasking of ground-based sensors for space situational awareness using deep reinforcement learning
Space situational awareness (SSA) is becoming increasingly challenging with the
proliferation of resident space objects (RSOs), ranging from CubeSats to mega …
proliferation of resident space objects (RSOs), ranging from CubeSats to mega …
Space-based sensor tasking using deep reinforcement learning
To maintain a robust catalog of resident space objects (RSOs), space situational awareness
(SSA) mission operators depend on ground-and space-based sensors to repeatedly detect …
(SSA) mission operators depend on ground-and space-based sensors to repeatedly detect …
Sensor tasking for space situation awareness: Combining reinforcement learning and causality
Tracking resident space objects (RSOs), which include functional and non-functional
satellites and space debris, requires flexible and adaptive tasking of sensors that operate in …
satellites and space debris, requires flexible and adaptive tasking of sensors that operate in …
[PDF][PDF] A deep reinforcement learning application to space-based sensor tasking for space situational awareness
TG Roberts, PM Siew, D Jang… - Proceedings of the 2021 …, 2021 - amostech.com
To maintain a robust catalog of resident space objects (RSOs), space situational awareness
(SSA) mission operators depend on ground-and space-based sensors to repeatedly detect …
(SSA) mission operators depend on ground-and space-based sensors to repeatedly detect …
Explainable deep reinforcement learning for space situational awareness: Counterfactual explanation approach
To effectively track resident space objects (RSOs), the tasking of sensors in a distributed
network requires flexible and adaptive approaches. While Deep Reinforcement Learning …
network requires flexible and adaptive approaches. While Deep Reinforcement Learning …
[PDF][PDF] Coordinated Space Domain Awareness as an Optimized Commodity Market
The convergence of autonomous robotic hardware and distributed sensor ecosystems is
revolutionizing surveillance technology and observational science. Next generation systems …
revolutionizing surveillance technology and observational science. Next generation systems …
[PDF][PDF] Cislunar space situational awareness sensor tasking using deep reinforcement learning agents
Cislunar space is gaining popularity with numerous missions being planned for the near
future. However, operating in the cislunar space domain poses additional risk to satellites …
future. However, operating in the cislunar space domain poses additional risk to satellites …