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International Journal of Aerospace Engineering
Volume 2017, Article ID 1235692, 17 pages
Research Article

Satellite Constellation Orbit Design Optimization with Combined Genetic Algorithm and Semianalytical Approach

1Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 305-701, Republic of Korea
2Korea Aerospace Research Institute (KARI), Daejeon 305-701, Republic of Korea

Correspondence should be addressed to Hyochoong Bang;

Received 27 February 2017; Revised 26 April 2017; Accepted 27 April 2017; Published 31 May 2017

Academic Editor: Christian Circi

Copyright © 2017 Tania Savitri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper focuses on maximizing the percent coverage and minimizing the revisit time for a small satellite constellation with limited coverage. A target area represented by a polygon defined by grid points is chosen instead of using a target point only. The constellation consists of nonsymmetric and circular Low Earth Orbit (LEO) satellites. A global optimization method, Genetic Algorithm (GA), is chosen due to its ability to locate a global optimum solution for nonlinear multiobjective problems. From six orbital elements, five elements (semimajor axis, inclination, argument of perigee, longitude of ascending node, and mean anomaly) are varied as optimization design variables. A multiobjective optimization study is conducted in this study with percent coverage and revisit time as the two main parameters to analyze the performance of the constellation. Some efforts are made to improve the objective function and to minimize the computational load. A semianalytical approach is implemented to speed up the guessing of initial orbital elements. To determine the best parametric operator combinations, the fitness value and the computational time from each study cases are compared.