Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Naomi Lee, Junior
Lead Presenter's Name
Naomi Lee
Lead Presenter's College
DB College of Arts and Sciences
Faculty Mentor Name
N/A
Abstract
The scope of this work explores biological swarm behavior and its application to low- and medium-sized Earth orbit satellite constellation systems. Existing constellation structures have predetermined orbits, meaning there is little adaptivity in the spacing and interactions between satellites. This allows for formation disruption by atmospheric perturbations in lower Earth orbit trajectories but can be countered with interactive controls that help with structure stability. This adaptive spacing and control can also be applied in MEO constellations in coverage and positioning optimization. In ‘mimicking’ this swarm behavior in starling murmurations, the separation, alignment, and cohesion flocking behavior of satellite groupings will be able to adapt quickly for most situations. The application of this motion to satellite constellations is modeled through simulation, where satellites are treated as agents that interact locally to maintain decentralized control and adaptive spacing. Using this swarm-based algorithm, we can optimize collision avoidance, create more flexible formation patterns, and lessen dependance on a more centralized control. By optimizing and maintaining efficient constellation geometries, satellite applications within Earth and space weather observation, defense, and communications can be significantly enhanced.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Included in
Multi-Vehicle Systems and Air Traffic Control Commons, Space Vehicles Commons, Systems Engineering and Multidisciplinary Design Optimization Commons
Applications of a Swarm-Behavior Model on Existing Satellite Constellations
The scope of this work explores biological swarm behavior and its application to low- and medium-sized Earth orbit satellite constellation systems. Existing constellation structures have predetermined orbits, meaning there is little adaptivity in the spacing and interactions between satellites. This allows for formation disruption by atmospheric perturbations in lower Earth orbit trajectories but can be countered with interactive controls that help with structure stability. This adaptive spacing and control can also be applied in MEO constellations in coverage and positioning optimization. In ‘mimicking’ this swarm behavior in starling murmurations, the separation, alignment, and cohesion flocking behavior of satellite groupings will be able to adapt quickly for most situations. The application of this motion to satellite constellations is modeled through simulation, where satellites are treated as agents that interact locally to maintain decentralized control and adaptive spacing. Using this swarm-based algorithm, we can optimize collision avoidance, create more flexible formation patterns, and lessen dependance on a more centralized control. By optimizing and maintaining efficient constellation geometries, satellite applications within Earth and space weather observation, defense, and communications can be significantly enhanced.