(Georgia Institute of Technology, 2015-12-01)
Snow, Adam C.
The proliferation of on-orbit debris has motivated much of the recent space situ ational awareness (SSA) missions and related research. Space-based missions are
typically carried out by large spacecraft, yet the emerging and improving technol ogy for CubeSat class satellites offers a potential new platform for SSA. This paper
presents the graduate Special Problem effort to develop explore the optimization
of a CubeSat constellation for SSA. This optimization approach considers two ob jectives: to maximize the number of daily unique detections while minimizing the
lifecycle cost of a constellation. The epsilon constraint method is used to devel op the Pareto Frontier with a genetic algorithm as the single-objective optimizer.
This work was prepared as part of a larger effort for the Journal of Spacecraft and
Rockets, and the supporting material is included.