… of the SSN and creating a need for new approaches for improving Space Situational
Awareness (SSA). SSA has become a key mission area for the US Air Force, which is tasked with …

… In this work, deep reinforcement learning (DRL) methods are leveraged to overcome the …
in the space situational awareness sensor tasking problem. An in-house SSA environment is …

… 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, …

… In this work, deep reinforcement learning (DRL) methods are … is inherent in space situational
awareness sensor tasking … -based training with an in-house developed SSA environment. …

… reinforcement learning. DRL agents rely on a different learning paradigm compared to
traditional machine learning … For example, by considering the nuances of reinforcement learning, …

The number of objects in LEO is expected to double in the next few years. The Space Situational
Awareness mission that had been carried out by USSPACECOM for decades has relied …

… of this research is to use deep reinforcement learning technique to create an autonomous
sensor tasking system capable of meeting the needs for Space Situational Awareness. …

… A foundational element of Space Situational Awareness (SSA) is the buildup and
maintenance of a catalog of the resident space objects (RSOs) orbiting the Earth. The object …

… Our SSA environment is a modified version of SSA Gym, an OpenAI Gym environment for
modeling the space situational awareness problem with orbital space objects, ground sensors, …

… Abstract—The main objective of this paper is to develop a novel reinforcement learning …
this objective as a deep reinforcement learning (RL) problem and training the RL agent on a …