Open AccessDesign Coverage Optimization Based on Position of Constellations and Cost of the Launch Vehicle
Author(s) -
Saeid Kohani,
Peng Zong,
Fengfan Yang
Publication year - 2021
Publication title -
wseas transactions on environment and development
Language(s) - English
Resource type - Journals
eISSN - 2224-3496
pISSN - 1790-5079
DOI - 10.37394/232015.2021.17.107
Subject(s) - constellation , satellite constellation , satellite , dilution of precision , computer science , position (finance) , genetic algorithm , matlab , orbit (dynamics) , global optimization , aerospace engineering , mathematical optimization , algorithm , mathematics , engineering , physics , gnss applications , machine learning , economics , operating system , finance , astronomy
This research will analyze the tradeoffs between coverage optimization based on Position dilution of precision (PDOP) and cost of the launch vehicle. It adopts MATLAB and STK tools along with multiple objective genetic algorithms (MOGA) to explore the trade space for the constellation designs at different orbital altitudes. The objective of optimal design solutions is inferred to determine the economic and efficient LEO, MEO, HEO or hybrid constellations and simulation results are presented to optimize the design of satellite constellations. The benefits of this research are the optimization of satellite constellation design, which reduces costs and increases regional and global coverage with the least number of satellites. The result of this project is the optimization of the number of constellation satellites in several orbital planes in LEO orbit. Validations are based on reviewing the results of several simulations. The results of graphs and tables are presented in the last two sections and are taken from the results of several simulations.