Optimal tasking of ground-based sensors for space situational awareness using deep reinforcement learning

HIGHLIGHTS

• who: Peng Mun Siew and Richard Linares from the Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA have published the paper: Optimal Tasking of Ground-Based Sensors for Space Situational Awareness Using Deep Reinforcement Learning, in the Journal: Sensors 2022, 22, 7847. of /2022/
• what: The authors focus on the catalog maintenance subproblem of the SSA task.
• future: Some of the proposed future works include extending the current SSA environment to support multiple sensors working together concurrently and improving the fidelity and realism of the SSA environment by incorporating . . .
  

   

  

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