Computer Simulation as an Effective Tool Supporting Decision-Making Processes in Air Defense (original) (raw)

The Application Of Simulation Technology To Military Command And Control Decision Support

2004

This paper reviews the application of simulation technology to military command and control decision support. A command and control system is defined and a model of decision-making is introduced. Possible applications of simulation to all phases of the command and control decision-making model are discussed. The difficulties of interfacing current C3I and simulation systems are outlined, and areas that require further research are identified.

Enhancing the Effectiveness of Air Defense Systems through Simulation Analysis

International Journal of Industrial and Manufacturing Engineering, 2020

Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years-in many cases, even decades-while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.

Modelling and Simulation in Defence

2003

The use of modelling and simulation (M&S) is becoming more pervasive throughout the NATO defence environment. Simulation models use a variety of techniques, which have evolved from system dynamics, information science and operations research (OR). There are closed simulations, without human interaction, which are used primarily for research and analysis. At the other end of the spectrum there are interactive simulations with considerably active participation of operators performing, in general, the human decision making process. The latter type has been the mainstay of experimental gaming or war gaming in the past, but is now finding increasing application in the computer-assisted exercises (CAX). Thus, it can be argued that, not only are simulation models and applications expanding, but that their associated techniques can be applied across the full spectrum of functional activities of armed forces.

Interactive Simulations in Support of Decision Making on Defence Resource Allocation

Information & Security: An International Journal, 2009

This article describes the approach and the experience of the Defence and Force Management Department at the -G.S. Rakovski‖ Defence and Staff College in conducting interactive simulations that support decision making on force structure, force development programs, and the respective allocation of resources. The primary purpose of the simulation is to educate students, mostly senior military and civilian MOD personnel, in the intricacies of defence planning in a changing environment, and to provide ‗hands on' experience in defence programming and budgeting. In addition, it allows exploring the space of potential policy alternatives, force structuring and programming decisions, thus serving as a powerful decision support tool.

Representing the Human Decision Making Process in Simulation Models of Combat

2003

Across NATO, there is a growing realisation that the proper representation of Command and Control (C2) within combat models is very important, in the context of major Defence topics such as Digitization of the Battlespace. In addition to the use of current OA models and tools to address immediate requirements, there is thus a need for longer term research to develop methods of properly representing these effects. In consequence, research has been instigated in the UK to investigate ways in which the effects of C2 can be incorporated successfully into constructive simulation models of combat i.e. models which can run in closed form on a computer, and represent the effects of C2, without the need for human intervention during the simulation run. wider span of scenarios in studies, reflecting increased uncertainty in the post-Cold War world. Another reflection of this uncertainty is the need to consider a wide range of sensitivity analysis. These point to the need for constructive simu...

Advanced aviation concepts via simulation: decision support for advanced aviation concepts

2002

This paper describes The MITRE Corporation Center for Advanced Aviation System Development (CAASD) research towards simulation of advanced aviation concepts. Research activities are aimed toward improving tactical and strategic decision making methods in the near and long term. We describe how CAASD simulation capabilities assist in determining how to achieve our goals for improving tactical and strategic decision making. For the long term, our simulation capabilities are becoming more agent-based.

New Measures of Effectiveness for the Air and Missile Defense Simulation Community

Phalanx Magazine: The Magazine of National Security Analysis, 2015

Modern Air and Missile Defense (AMD) systems use radar paired with a gun or missile weapon system to detect and destroy an array of threat types that includes theater ballistic missiles (TBMs), cruise missiles (CMs), and unmanned aerial systems (UASs). The typical Measure of Effectiveness (MOE) used in most AMD analyses is a single number that represents the total quantity of incoming threats that were not shot down, also known as “leakers.” This single number does not provide enough fidelity for current and future analyses where the incoming threat raid (group of threat systems) will be a large number of threats made up of a mix of the three system types. To properly evaluate such large and complex raids, analysts need additional MOEs that quantify the effects of the raid and the risk of not being able to execute the simulated concept of the operation (CONOP) amongst the fog and friction of war. To quantify these effects, analysts should compute the total weight of ordnance that impacts the defended asset as well as the number of leakers by threat system type. To quantify the risk, analysts should measure the engagement window and the decision time that a commander has for each type of threat. Together, these new MOEs allow analysts and commanders to better compare different CONOPs for AMD systems based on the effects of an enemy attack and the risk to friendly forces.

Achieving realistic performance and decison-making capabilities in computer-generated air forces

Modeling, Simulation, and Visualization of Sensory Response for Defense Applications, 1997

For a computer-generated force (CGF) system to be useful in training environments, it must be able to operate at multiple skill levels, exhibit competency at assigned missions, and comply with current doctrine. Because ofthe rapid rate cf change in Distributed Interactive Simulation (DIS) and the expanding set of performance objectives for any computergenerated force, the system must also be modifiable at reasonable cost and incorporate mechanisms for learning. Therefore, CGF applications must have adaptable decision mechanisms and behaviors and perform automated incorporation of past reasoning and experience into its decision process. The CGF must also possess multiple skill levels for classes of entities, gracefully degrade its reasoning capability in response to system stress, possess an expandable modular knowledge structure, and perform adaptive mission planning. Furthermore, correctly performing individual entity behaviors is not sufficient. Issues related to complex inter-entity behavioral interactions, such as the need to maintain formation and share information, must also be considered. The CGF must also be able to acceptably respond to unforeseen circumstances and be able to make decisions in spite ofuncertain information. Because ofthe need for increased complexity in the virtual battlespace, the CGF should exhibit complex, realistic behavior patterns within the battlespace.