Optimal Satellite Orbit Design for Prioritized Multiple Targets with Threshold Observation Time Using Self-Adaptive Differential Evolution
Publication: Journal of Aerospace Engineering
Volume 28, Issue 2
Abstract
This study considers a satellite orbit design when a given set of target sites needs to be visited within an assigned period. Optimization of the orbit design takes into account target properties such as priority and minimum duration of observation time. Equations describing satellite orbit are used to compute the satellite’s field of view and ground track. Scheduling of visits to the targets is carried out by maximizing the observation time over priority-weighted targets and minimizing the distance between the ground track and the target position while satisfying the constraints with respect to the minimum duration of observation time and revisit requirement. A self-adaptive differential evolution (SA-DE) algorithm with the ability to adjust its search parameters is used to find the best solution. The proposed design methodology computes the optimal values of design variables and also the start and end observation time points of each target. Regional and global case studies demonstrate that the SA-DE/best/1/bin variant is found to be the most suitable optimizer for orbit design.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This study was supported by the National Natural Science Foundation of China (Grant No. 71071156 and 70971131) and McMaster University.
References
Abdelkhalik, O. (2010). “Initial orbit design from ground track points.” J. Spacecr. Rockets, 47(1), 202–205.
Abdelkhalik, O., and Gad, A. (2011). “Optimization of space orbits design for earth orbiting missions.” Acta Astronaut., 68(7–8), 1307–1317.
Abdelkhalik, O., and Mortari, D. (2006). “Orbit design for ground surveillance using genetic algorithms.” J. Guid. Contr. Dynam., 29(5), 1231–1233.
Cacciatore, F., and Toglia, C. (2008). “Optimization of orbital trajectories using genetic algorithms.” J. Aerosp. Eng., Sci. Appl., 1(1), 58–69.
Gad, A., and Abdelkhalik, O. (2009). “Repeated shadow track orbits for space-sunsetter missions.” Int. J. Aerosp. Eng., 2009, 561495.
Hall, T. S. (2010). “Orbit maneuver for responsive coverage using electric propulsion.” M.S. thesis, School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH.
Howard, D. C. (2009). Orbital mechanics for engineering students, 2nd Ed., Butterworth-Heinemann, Oxford, U.K.
Justin, M. A., Tyler, N. T., Reece, T. I., Jason, T. A., Wayne, A. S., and Joseph, M. C. (2008). “CubeSat-based disaster detection and monitoring systems (AIAA-RS6-2008–2006).” Proc., 6th Responsive Space Conf., NovaSol, Honolulu, HI, 1–5.
Kim, H. D., Bang, H., and Jung, O. C. (2008). “A heuristic approach to the design of an orbit for a temporary reconnaissance mission using a few LEO satellites.” AAS/AIAA Space Flight Mechanics Meeting, American Institute of Aeronautics and Astronautics, Reston, VA.
Kim, Y. H., and Spencer, D. B. (2002). “Optimal spacecraft rendezvous using genetic algorithms.” J. Spacecr. Rockets, 39(6), 859–865.
Lampinen, J., and Zelinka, I. (1999). “Mixed variable non-linear optimization by differential evolution.” Proc., 5th Int. Conf. on Soft Computing, Proc., Nostradamus, 99(2), 7–8.
Price, K., Storn, R., and Lampinen, J. (2005). Differential evolution: A practical approach to global optimization, Springer, New York.
Storn, R., and Price, K. (1997). “Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces.” J. Global Optimiz., 11(4), 341–359.
Vallado, D. A. (2007). Fundamental of astrodynamics and applications, 3rd Ed., Microcosm Press, Hawthorne, CA.
Vasileios, O. (2012). “Optimal orbital coverage of theater operations and targets.” Appl. Math. Inform. Military Sci., 71, 151–186.
Vesterstrom, J., and Thomsen, R. (2004). “A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems.” IEEE Evolutionary Computation Congress, Vol. 2, Institute of Electrical and Electronics Engineers, Piscataway, NJ, 1980–1987.
Vtipil, S., and Newman, B. (2010). “Designing a constrained optimal orbit for Earth observation satellites based on user requirements (AIAA 2010–7520).” AIAA/AAS Astrodynamics Specialist Conf., Curran Associates, New York, 1–16.
Wagner, C. (1991). “A prograde geosat exact repeat mission.” J. Astronaut. Sci., 39(3), 313–326.
Wall, B. J., and Conway, B. A. (2009). “Genetic algorithms applied to the solution of hybrid optimal control problems in astrodynamics.” J. Global Optimiz., 44(4), 493–508.
Wolfe, W. J., and Sorensen, S. E. (2000). “Three scheduling algorithms applied to the earth observing systems domain.” Manage. Sci., 46(1), 148–168.
Zamuda, A., Brest, J., Boskovic, B., and Zumer, V. (2007). “Differential evolution for multiobjective optimization with self adaptation.” The 2007 IEEE Congress on Evolutionary Computation, Institute of Electrical and Electronics Engineers, Piscataway, NJ, 3617–3624.
Information & Authors
Information
Published In
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Mar 25, 2013
Accepted: Oct 15, 2013
Published online: Oct 17, 2013
Discussion open until: Dec 7, 2014
Published in print: Mar 1, 2015
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.