Abstract
The increasing demand for low-cost space-borne Earth observation missions has led to small satellite constellation systems development. CubeSat platforms can provide a cost-effective multiple-mission space system using state-of-the-art technology. This paper presents a new approach to CubeSat constellation design for multiple missions using a multi-objective genetic algorithm (MOGA). The CubeSat constellation system is proposed to perform multi-missions that should satisfy global Earth observation and regional disaster monitoring missions. A computational approach using a class of MOGA named non-dominated sorting genetic algorithm II is implemented to optimize the proposed system. Pareto optimal solutions are found that can minimize the number of satellites and the average revisit time (ART) for both regional and global coverage while maximizing the percentage coverage. As a result, the study validates the feasibility of implementing the CubeSat constellation design with an acceptable level of performance in terms of ART and percentage coverage. Moreover, the study demonstrates CubeSat’s ability to perform a multi-missions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
