Session
Pre-Conference Posters Session I
Location
Utah State University, Logan, UT
Abstract
This paper will review results and discuss a novel method to address the multiple-objective optimization problem of ground station placement; enabling continuous communication with the mega constellation defined in Optimized Continuous Global Coverage Constellation using a Genetic Algorithm. A genetic algorithm implemented in MATLAB explored the globe utilizing Satellite Tool Kit to determining the optimal number of ground stations and their placement – considering local infrastructure available and the constellation connectivity during a 24-hour period. A new revenue-based fitness function evaluated these parameters and the potential revenue to determine the most profitable configuration.
Optimized Ground Station Placement for a Mega Constellation using a Genetic Algorithm
Utah State University, Logan, UT
This paper will review results and discuss a novel method to address the multiple-objective optimization problem of ground station placement; enabling continuous communication with the mega constellation defined in Optimized Continuous Global Coverage Constellation using a Genetic Algorithm. A genetic algorithm implemented in MATLAB explored the globe utilizing Satellite Tool Kit to determining the optimal number of ground stations and their placement – considering local infrastructure available and the constellation connectivity during a 24-hour period. A new revenue-based fitness function evaluated these parameters and the potential revenue to determine the most profitable configuration.
