Phenomenological modeling and simulation in support of model abstraction: computational electromagnetics--an overview

Donald R. Pflug

doi:10.1117/12.351189

22 June 1999 Phenomenological modeling and simulation in support of model abstraction: computational electromagnetics--an overview

Donald R. Pflug

Author Affiliations +

Proceedings Volume 3696, Enabling Technology for Simulation Science III; (1999) https://doi.org/10.1117/12.351189
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

Successful modeling and simulation of Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) systems requires not only the inclusion of the relevant C4ISR processes involved in the problem under study but also inclusion of the physics behind some of the simulation objects. The electromagnetic performance of the various sensors present in the simulation and the electromagnetic effects caused by the platforms on which the sensors reside are examples. The physical science necessary to simulate such physical effects is called Computational Electromagnetics (CEM) and can provide high quality performance data capable of enhancing the accuracy and value of C4ISR simulations. Unfortunately the simulation of these effects from first principles cannot be done in even near real time. Model Abstraction needs to be applied to such phenomenological simulations to extract out data of the required accuracy in reasonable simulation time. This paper reviews state-of-the-art CEM with a view towards stimulating the development of those Model Abstraction techniques required to incorporate CEM phenomenology into the C4ISR modeling and simulation world.

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Donald R. Pflug "Phenomenological modeling and simulation in support of model abstraction: computational electromagnetics--an overview", Proc. SPIE 3696, Enabling Technology for Simulation Science III, (22 June 1999); https://doi.org/10.1117/12.351189

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KEYWORDS

Electromagnetism

Computer simulations

Antennas

Computing systems

Data modeling

Maxwell's equations

Modeling and simulation

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