Abstract
This chapter introduces novel integrated management of multiple heterogeneous satellite missions for the purpose of intelligence collection. The focus is on optimization of acquisition planning and scheduling for various missions including single satellites and satellite constellations. The relevant optimization problem and its mathematical programming formulation that allow multiple area coverage plans for each acquisition request, as well as consideration of the quality measures of coverage plan, strip, and imaging opportunity, are presented. The chapter consists of a multi-mission planning system overview, a survey of relevant literature, a definition of the integrated acquisition scheduling optimization problem and its mathematical programming formulation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Augenstein, S.: Optimal scheduling of Earth-imaging satellites with human collaboration via directed acyclic graphs. In: The Intersection of Robust Intelligence and Trust in Autonomous Systems: AAAI Spring Symposium, 2014
Benoist, T., Rottembourg, B.: Upper bounds of the maximal revenue of an earth observation satellite. 4OR: Quart. J. Belgian, French and Italian Oper. Res. Soc. 2(3), 235–249 (2004)
Bensana, E., Verfaillie, G., Agnese, J.C., Bataille, N., Blumstein, D.: Exact and inexact methods for the daily management of an earth observation satellite. In: Proceedings of the 4th International Symposium on Space Mission Operations and Ground Data Systems (SpaceOps-96), Munich, Germany, 1996
Bianchessi, N., Cordeau, J.-F., Desrosiers, J., Laporte, G., Raymond, V.: A heuristic for the multi-satellite, multi-orbit and multi-user management of earth observation satellites. Eur. J. Oper. Res. 177, 750–762 (2007)
Cordeau, J.-F., Laporte, G.: Maximizing the value of an earth observation satellite orbit. J. Oper. Res. Soc. 56(8), 962–968 (2005)
Dishan, Q., Chuan, H., Jin, L., Manhao, M.: A dynamic scheduling method of earth-observing satellites by employing rolling horizon strategy. Sci. World J. 2013, 1–11 (2013)
Farr, T.G.: Chapter 5: Radar interactions with geologic surface. In Guide to Magellan Image Interpretation, NASA and Jet Propulsion Laboratory, California Institute of Technology, 1993
Fisher, W.: The optiwise corporation deconfliction scheduler algorithms (as used in STK/Scheduler). Optwise (2004)
Fisher, W.A., Herz, E.: A flexible architecture for creating scheduling algorithms as used in STK scheduler. White paper, Optwise Corporation and Orbit Logic Incorporated, 2013
Frank, J., Jonsson, A., Morris, R., Smith, D.: Planning and scheduling for fleets of earth observing satellites. In: Proceedings of the 6th International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS-01), Montreal, Canada, 2001
Gabrel, V., Murat, C.: Mathematical programming for earth observation satellite mission planning. In: Ciriani, T., Fasano, G., Gliozzi, S., Tadei, R. (eds.) Operations Research in Space and Air, pp. 103–122. Kluwer, Dordrecht (2003)
Gabrel, V., Vanderpooten, D.: Enumeration and interactive selection of efficient paths in a multiple criteria graph for scheduling an earth observing satellite. Eur. J. Oper. Res. 139, 533–542 (2002)
Gabrel, V., Moulet, A., Murat, C., Paschos, V.: A new single model and derived algorithms for the satellite shot planning problem using graph theory concepts. Ann. Oper. Res. 69, 115–134 (1997)
Globus, A., Crawford, J., Lohn, J., Pryor, A.: Scheduling earth observing satellites with evolutionary algorithms. In: Proceedings of the 1st International Conference on Space Mission Challenges for Information Technology (SMC-IT-03), Pasadena, CA, 2003
Globus, A., Crawford, J., Lohn, J., Morris, R.: A comparison of techniques for scheduling earth observing satellites. In: Proceedings of the 16th Conference on Innovative Applications of Artificial Intelligence (IAAI-04), San Jose, CA, 2004
Hall, N., Magazine, M.: Maximizing the value of a space mission. Eur. J. Oper. Res. 78, 224–241 (1994)
Hwang, F.-T., Yeh, Y.-Y., Li, S.-Y.: Multi-objective optimization for multi-satellite scheduling system. In: Proceedings of 31st Asian Conference on Remote Sensing 2010 (ACRS 2010), Hanoi, 1–5 Nov (2010)
Lemaitre, M., Verfaillie, G., Jouhaud, F., Lachiver, J.M., Bataille, N.: How to manage the new generation of agile earth observation satellites. In: Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, pp. 1–10 (2000)
Lemaitre, M., Verfaillie, G., Jouhaud, F., Lachiver, J.-M., Bataille, N.: Selecting and scheduling observations of agile satellites. Aerosp. Sci. Technol. 6, 367–381 (2002)
Liao, D., Chang, Y.: Imaging order scheduling of an Earth observation satellite. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 37(5), 794–802 (2007)
Lin, W., Liao, D., Liu, C., Lee, Y.: Daily imaging scheduling of an earth observation satellite. IEEE Trans. Syst. Man Cybern. 35(2), 213–223 (2005)
Lin, W.C., Chang, S.C.: Hybrid algorithms for satellite imaging scheduling. In: 2005 IEEE International Conference on Systems, Man and Cybernetics, Waikoloa, 10–12 Oct 2005
Malladi, K.T., Mitrovic-Minic, S, Karapetyan, D., Punnen, A.P.: Satellite constellation image acquisition problem: a case study. In: Fasano G., Pinter J.D. (eds.) Space Engineering: Modelling and Optimization with Case Studies. Springer (2016)
Malladi, K.T., Mitrovic-Minic, S., Punnen, A.P.: Cluster restricted maximum weight clique problem: algorithms and empirical analysis. Comput. Oper. Res. 85, 113–128 (2017)
Mitrovic-Minic, S., Punnen, A.P.: Very large-scale variable neighborhood search for the generalized assignment problem. Journal of Interdisciplinary Mathematics. 11(5), 653–670 (2008)
Mitrovic-Minic, S., Punnen, A.P.: Variable intensity local search. Annals of Information Systems. 10, 245–252 (2009)
Mitrovic-Minic, S., Punnen, A.P.: Local search intensified: very large-scale variable neighborhood search for the multi-resource generalized assignment problem. Discret. Optim. 6, 370–377 (2009)
Mitrovic-Minic, S., Berger, J., Thomson, D.: Collection Planning Management: Multi-Satellite Collection Scheduling. MDA, CR, DRDC-RDDC-2016-C309 (2016)
Muraoka, H., Cohen, R., Ohno, T., Doi, N.: ASTER observation scheduling algorithm. In: Proceedings of the 5th International Symposium on Space Mission Operations and Ground Data Systems (SpaceOps-98), Tokyo, Japan, 1998
Nelson, F.N.: Scheduling optimization for imagery satellite constellations using column generation. PhD Thesis, Department of Systems Engineering and Operations Research, Volgenau School of Engineering, George Mason University (2012)
Pemberton, J.: Towards scheduling over-constrained remote sensing satellites. In: Proceedings of the 2nd NASA International Workshop on Planning and Scheduling for Space, pp. 84–89, San Francisco, CA, 2000
Pixalytics. https://www.pixalytics.com/sats-orbiting-earth-2017/ (2017)
Secker, J., Robson, M., Rowe, J., Vachon, P.W.: Automated acquisition planning for commercial satellite imagery. In: IEEE International Conference on Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006, pp. 3279–3282 (2006)
Tangpattanakul, P., Jozefowiez, N., Lopez, P.: A multi-objective local search heuristic for scheduling earth observations taken by an agile satellite. Eur. J. Oper. Res. 245, 542–554 (2015)
Vachon, P.W., Secker, J., Werle, D.: Remote sensing in support of Arctic intelligence: Development of sensor selection rules. DRDC Ottawa TM 2007–109 (2007)
Vasquez, M., Hao, J.K.: A logic-constrained knapsack formulation and a Tabu algorithm for the daily photograph scheduling of an earth observation satellite. Journal of Computational Optimization and Applications. 20(2), 137–157 (2001)
Vasquez, M., Hao, J.K.: Upper bounds for the SPOT 5 daily photograph scheduling problem. J. Comb. Optim. 7, 87–103 (2003)
Verfaillie, G.: Planning and scheduling activities for earth surveillance and observation satellites: a constraint-based perspective. In: ICAPS 2013 Summer School, Perugia, 4–7 June 2013
Verfaillie, G., Lemaitre, M.: Planning and scheduling activities for earth surveillance and observation satellites: a constraint-based perspective. In: ICAPS Tutorial 2006, Cumbria, 2006
Verfaillie, G., Lemaitre, M., Schiex, T.: Russian doll search for solving constraint optimization problems. In: Proceedings of the 13th National Conference on Artificial Intelligence (AAAI-96), pp. 181–187. Portland 1996
Wang, J., Demeulemeester, E., Qiu, D., Liu, J.: Exact and inexact scheduling algorithms for multiple earth observation satellites under uncertainties of clouds. In: Technical Chapter KBI_1514, KU Leuven, Faculty of Economics and Business, Preprint submitted to EJOR on 1 July 2015
Wang, P., Tan, Y., Reinelt, G.: A comparison of heuristic methods for scheduling Earth observing satellites fleet. In: Proceedings of 2009 International Conference on Information Technology and Computer Science, Kiev, 25–26 July 2009
Wolfe, W., Sorensen, S.: Three scheduling algorithms applied to the earth observing systems domain. Manag. Sci. 46(1), 148–168 (2000)
Wu, G., Wang, H., Li, H., Pedrycz, W., Qiu, D., Ma, M., Liu, J.: An adaptive simulated annealing-based satellite observation scheduling method combined with a dynamic task clustering strategy. Comput. Res. Repos. (2014). https://arxiv.org/abs/1401.6098
Xiaolu, L., Baocun, B., Yingwu, C., Feng, Y.: Multi satellites scheduling algorithm based on task merging mechanism. Appl. Math. Comput. 230, 687–700 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix: Survey Summary
Appendix: Survey Summary
Table 1 summarizes the literature survey presented in this chapter. The manuscripts are grouped by the solution approach in the following manner: exact methods, heuristics and metaheuristics, constraint programming, and bounds. Within each group, the manuscripts are listed chronologically.
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Mitrovic-Minic, S., Thomson, D., Berger, J., Secker, J. (2019). Collection Planning and Scheduling for Multiple Heterogeneous Satellite Missions: Survey, Optimization Problem, and Mathematical Programming Formulation. In: Fasano, G., Pintér, J. (eds) Modeling and Optimization in Space Engineering . Springer Optimization and Its Applications, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-030-10501-3_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-10501-3_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-10500-6
Online ISBN: 978-3-030-10501-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)