Abstract
As the complexity of military operations increases, the defense modeling and simulation (DM&S) has contributed in analytically improving doctrines at the engineering, engagement, mission, and campaign levels. To date, defense modelers concentrate on the best representation of their targeted system at their targeted modeling level, and the modelers have parameterized and abstractly represented features that are not the prime concerns of their modeling level. However, insights from the battle experiment using such models are limited by the represented world of the model; the modelers are missing potential insights that might be gained if the modelers included more features in the simulation. Hence, to gain missed insights, this case study illustrates a battle experiment framework via the simulation interoperation of the heterogeneous levels of models. Our application is developing a mission-level doctrine for naval air defense scenarios, but a mission-level model alone does not represent the whole picture of the scenarios, and the model represents only the command and control procedures in detail, not the mechanical and engagement-level features. On the other hand, an engagement-level model depicts some of the missing parts of the scenarios in the mission-level model. Our finding is that we can gain new insights from performing battle experiments by interoperating two such models at the mission and engagement levels. Through the interoperation, input values of the mission-level model are generated from the engagement-level model dynamically, whereas the values were predefined parameters without the interoperation in the past. This dynamic value feed enables capture of the missing parts of the modeled scenarios at the mission level, eventually leading us to new insights. To demonstrate this improvement, this case study illustrates the different findings between the single model runs with predefined parameters and the interoperation model with dynamically generated parameters. We expect that this work will provide a new methodology for battle experiments by extending the limitation of single model representation of the real world.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
This case study is initially published by Simulation: Transactions of the Society for Modeling and Simulation, International (Kim et al. 2012). This chapter expands the original article by expanding the model description and discussion in conjunction with the command and control research. Additionally, this chapter includes the discussion of utilizing formalism in the agent-based modeling to compare this case study to the case study presented in Chap. 2.
References
Bernard, P.Z., Herbert, P., Kim, T.G.: Theory of modeling and simulation, 2nd edn. Academic Press, New York (2000)
Calfee, S.H.: Autonomous agent-based simulation of an AEGIS cruiser combat information center performing battle group air-defense commander operations. M.S. Thesis, Naval Postgraduate School (2003)
Calfee, S.H., Rowe, N.C.: Multi-agent simulation of human behavior in naval air defense. Naval Eng. J. 116(4), 53–64 (2004)
Carley, K.M., Lin, Z.: Organizational designs suited to high performance under stress. IEEE Trans. Syst. Man Cybern. 25(2), 221–230 (1995)
Committee on Technology for Future Naval Forces, National Research Council: Creating and improving intellectual and technological infrastructure for M&S. Technology for the United States navy and marine corps, 2000–2035: becoming a 21st-century force: vol. 9: modeling and simulation. National Academy of Sciences. Chap. 6, pp. 70–90 (1997)
Cramer, M.A., Beach, J.E., Mazzuchi, T.A., Sarkani, S.: Understanding information uncertainty within the context of a net-centric data model: a mine warfare example. 13th ICCRT. Paper: I-203 (2008)
Davis, P.K.: Exploratory analysis enabled by multiresolution, multiperspective modeling. In: 2000 Winter Simulation Conference, vol. 1, pp. 293–302 (2000)
Davis, P.K.: Introduction to multiresolution, multiperspective modeling (MRMPM) and exploratory analysis. Working paper. RAND (2005)
Davis, P. K., Hillestad, R.: Families of models that cross levels of resolution: issues for design, calibration and management. In: Proceedings of the 25th Conference on Winter Simulation, pp. 1003–1012 (1993)
Department of Defense, Office of the Under Secretary of Defense for Acquisition, Technology and Logistics: Acquisition modeling and simulation master plan. Systems Engineering Forum (2006)
Department of the Navy: Sea power for a new era 2007, a program guide to the U.S. Navy. http://www.navy.mil/policy/seapower/spne07/to-spone07.html (2007)
Fishwick, P.A., Hari, N., Jon, S., Andrea, B.: A multimodel approach to reason-ing and simulation. IEEE Trans. Syst. Man Cybern. 24, 1433–1449 (1994)
Harrison, N., Gilbert, B., Lauzon, M., Jeffrey, A., Lalancette, C., Lestage, R., Morin, A.: A M&S process to achieve reusability and interoperability. In: RTO NMSG Conference (2002)
Huntsville: EADSIM execute summary. http://www.eadsim.com. Teledyne Brown Engineering, INC, Alabama (2000)
IEEE Std 1516: IEEE standard for modeling and simulation (M&S) high level architecture (HLA)—framework and rules (2000)
Kim, T.G., Sung, C.H., Hong, S-.Y., Hong, J.H., Choi, C.B., Kim, J.H., Seo, K.M., Bae, J.W.: DEVSim++ toolset for defense modeling and simulation and interoperation. J. Defense Model. Simul. Appl. Methodol. Technol. 8(3), 129–142, July (2011)
Kim, J., Moon, I. C., Kim, T.G.: New insight into doctrine via simulation interoperation of heterogeneous levels of models in battle experimentation. Simul. Trans. Soc. Model. Simul. Int. 88(6), 649–667 (2012)
Lalis, V.: Exploring naval tactics with UAVs in an Island complex using agent-based simulation. M.S. Thesis, Naval Postgraduate School (2007)
Levent, Y., Alvin, L., Simon, B., Tuncer, Ö.: Requirements and design principles for multiresolution, multistage multimodels. In: Henderson, S.G., Biller, B., Hsieh, M.-H., Shortle, J., Tew, J.D., Barton, R.R. (eds.) Proceedings of the 2007 Winter Simulation Conference, pp. 823-832 (2007)
Liebhaber, M.J., Smith, C.A.P.: Naval air defense threat assessment: cognitive factors and model. In: Command and Control Research and Technology Symposium (2000)
Manclark, J.: Air force test and evaluation presentation. U.S. Air Force T&E Days 2009 (2009)
Maurice, A.: Assessing the treatment of airborne tactical high energy lasers in combat simulations. M.S. Thesis, Air Force Institute of Technology (2003)
Michael, R.H.: Using army force-on-force simulations to stimulate C4I systems for testing and experimentation. In: Command and Control Research and Technology Symposium, ICCRTS. Paper: I-077 (1999)
Neary, C.J.: Navy surface tactical missiles. In: AIAA Strategic and Tactical Missile Systems Conference. Unclassified Presentation (2008)
OzKan, B., Rowe, N.C., Carfee, S.H., Hiles, J.E.: Three simulation models of naval air defense. 10th ICCRTS. Paper:I-194 (2005)
Piplani, L.K., Mercer, J.G., Roop, R.O.: Systems acquisition manager’s guide for the use of models and simulations. Report of the DSMC 1993–1994. Defense Systems Management College, Fort Belvoir, Virginia (1994)
RTO NATO Modeling and Simulation Group (NMSG): M&S support to assessment of extended air defence C2 interoperability. RTO technical report (2004)
SAICTR Group: High level architecture run-time infrastructure RTI 1.3-next generation programmer’s guide version 5. DMSO (1999)
Simulation Interoperability Standards Organization: http://www.sisostds.org/ (2012)
Stevens, W.K., Decker, W.L., Gagnon, C.M.: Representation of command and control (C2) and information operations (IO) in military simulations. In: Proceedings of the NATO Studies, Analysis and Simulation Panel (SAS) 1999 Symposium on Modeling and Analysis of Command and Control (1999)
Sung, C.H., Hong, J.H., Kim, T.G.: Interoperation of DEVS models and differential equation models using HLA/RTI: hybrid simulation of engineering and engagement level models. In: 2009 Spring Simulation Multi Conference (2009)
Zavarelli, J., De Chiaro, S. A., Fournier, J., Schweickert, D.A., Zislin, A.: Live virtual constructive experiments for C2 evaluation. 11th ICCRTS. Paper: I-090 (2006)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 Il-Chul Moon
About this chapter
Cite this chapter
Moon, IC., Carley, K.M., Kim, T.G. (2013). Modeling and Simulating Command and Control for Naval Air Defense Operation. In: Modeling and Simulating Command and Control. SpringerBriefs in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-5037-4_3
Download citation
DOI: https://doi.org/10.1007/978-1-4471-5037-4_3
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-5036-7
Online ISBN: 978-1-4471-5037-4
eBook Packages: Computer ScienceComputer Science (R0)