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 …

[PDF][PDF] SSA sensor tasking: comparison of machine learning with classical optimization methods

BD Little, C Frueh - Proceedings of the Advanced Maui Optical and …, 2018 - amostech.com
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 those …

[引用][C] Sensor scheduling using ant colony optimization

D Schrage, PG Gonsalves - Sixth International Conference of …, 2003 - ieeexplore.ieee.org
The basic problem of collection management is to schedule a group of sensor assets over a
series of mission objectives in a way that minimizes resource usage and maximizes the …

[PDF][PDF] Sensor tasking for multi-sensor space object surveillance

C Frueh - Seventh European Conference on Space …, 2017 - conference.sdo.esoc.esa.int
Efficient sensor tasking is a crucial step in building up and maintaining a catalog of space
objects at the highest possible orbit quality. With increased sensing capabilities, also the …

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 …

[PDF][PDF] Dynamic sensor tasking for space situational awareness via reinforcement learning

R Linares, R Furfaro - Advanced Maui Optical and Space …, 2016 - amostech.com
This work provides the RL method with a negative reward as long as any SO has a total
position error above the uncertainty threshold. This penalizes policies that take longer to …

Learning-based airborne sensor task assignment in unknown dynamic environments

J He, Y Wang, Y Liang, J Hu, S Yan - Engineering Applications of Artificial …, 2022 - Elsevier
In sensor management, the existing researches rely on traditional system modeling and
strive to maximize the information superiority. In fact, on the one hand, complex …

A greedy ant colony system for defensive resource assignment problems

MD Rezende, BSLP De Lima… - Applied Artificial …, 2018 - Taylor & Francis
The weapon-target assignment (WTA) problem is crucial for strategic planning in military
decision-making operations. It defines the best way to assign defensive resources against …

Evolutionary sensor allocation for the Space Surveillance Network

GH Greve, KM Hopkinson… - The Journal of Defense …, 2018 - journals.sagepub.com
The congested exosphere continues to contain more satellites and debris, raising the
potential for destructive collisions. The Special Perturbations (SP) Tasker algorithm currently …

Autonomous situational awareness for UAS swarms

VW Hill, RW Thomas, JD Larson - 2021 IEEE Aerospace …, 2021 - ieeexplore.ieee.org
This paper describes a technique for the autonomous mission planning of unmanned aerial
system swarms. Given a swarm operating in a known area, a central command system …