Deep learning methods for space situational awareness in mega-constellations satellite-based internet of things networks
F Massimi, P Ferrara, F Benedetto - Sensors, 2022 - mdpi.com
Artificial Intelligence of things (AIoT) is the combination of Artificial Intelligence (AI)
technologies and the Internet of Things (IoT) infrastructure. AI deals with the devices' …
technologies and the Internet of Things (IoT) infrastructure. AI deals with the devices' …
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 …
Sensor tasking in the cislunar regime using Monte Carlo Tree Search
S Fedeler, M Holzinger, W Whitacre - Advances in Space Research, 2022 - Elsevier
Maintaining tracks on space objects with limited sets of observers is a critical problem, made
more urgent with exponential growth in the population of near-Earth satellites. An optimally …
more urgent with exponential growth in the population of near-Earth satellites. An optimally …
Heuristic and optimized sensor tasking observation strategies with exemplification for geosynchronous objects
C Frueh, H Fielder, J Herzog - Journal of Guidance, Control, and …, 2018 - arc.aiaa.org
With the new space fence technology, the catalog of known space objects is expected to
increase to the order of 100,000 objects. Objects need to be initially detected, and sufficient …
increase to the order of 100,000 objects. Objects need to be initially detected, and sufficient …
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 situational awareness sensor tasking: comparison of machine learning with classical optimization methods
BD Little, CE Frueh - Journal of Guidance, Control, and Dynamics, 2020 - arc.aiaa.org
The object population in the space around the Earth is subject to increase. With the
advancements in sensor capabilities, it can be expected that, at the same time, more of …
advancements in sensor capabilities, it can be expected that, at the same time, more of …
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] An autonomous sensor tasking approach for large scale space object cataloging
Abstract The field of Space Situational Awareness (SSA) has progressed over the last few
decades with new sensors coming online, the development of new approaches for making …
decades with new sensors coming online, the development of new approaches for making …
Spacecraft command and control with safety guarantees using shielded deep reinforcement learning
AT Harris, H Schaub - AIAA Scitech 2020 Forum, 2020 - arc.aiaa.org
Increasingly complex space missions have motivated the development of autonomous
command and control approaches which must handle high-dimensional, continuous …
command and control approaches which must handle high-dimensional, continuous …