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Operator training using a weapon in a real-world environment is risky, expensive, time-consuming, and restricted to the given environment. In addition, governments are under intense scrutiny to provide security, yet they must also strive for efficiency and reduce spending. In other words, they must do more with less. Virtual simulation, is usually employed to solve these limitations. As the operator is trained to maximize weapon effectiveness, the effectiveness-focused training can be completed in an economical manner. Unfortunately, the training is completed in limited scenarios without objective levels of training factors for an individual operator to optimize the weapon effectiveness. Thus, the training will not be effective. For overcoming this problem, we suggest a methodology on guiding effectiveness-focused training of the weapon operator through usability assessments, big data, and Virtual and Constructive (VC) simulations.

The modeling and simulation pyramid in defense states it clearly: Multi-Level modeling and simulation are required. Models and simulations are often classified by the US Department of Defense into four levels—campaign, mission, engagement, and engineering. Campaign simulation models are applied for evaluation; mission-level simulations to experiment with the integration of several macro agents; engagement simulations in engineered systems development; and engineering-level simulation models with a solid foundation in structural physics and components. Models operating at one level must be able to interact with models at another level. Therefore, the cure (“silver bullet”) is very clear: a comprehensive framework for Multiple Resolution Modeling (MRM) is needed. In this paper, we discuss our research about how to construct MRM environments.

Multi-Resolution Modeling (MRM) is one of the key technologies for building complex and large-scale simulations using legacy simulators. MRM has been developed continuously, especially in military fields. MRM plays a crucial role to describe the battlefield and gathering the desired information efficiently by linking various levels of resolution. The simulation models interact across different local and/or distance area networks using the High Level Architecture (HLA) regardless of their operating systems and hardware. The HLA is a standard architecture developed by the US Department of Defense (DoD) and is meant to create interoperability among different types of simulators. Therefore, MRM implementations are very dependent on Interoperability and Composability. This paper summarizes the definition of MRM-related terminology and proposes a basic form of MRM system using Commercial Off-The-Shelf (COTS) simulators and HLA.

The Weapon Combat Effectiveness (WCE) analytics is very expensive, time-consuming, and dangerous in the real world because we have to create data from the real operations with a lot of people and weapons in the actual environment. The Modeling and Simulation (M&S) of many techniques are used for overcoming these limitations. Although the era of big data has emerged and achieved a great deal of success in a variety of fields, most of WCE research using the Defense Modeling and Simulation (DM&S) techniques studied have considered a lot of assumptions and limited scenarios without the help of big data technologies. Furthermore, WCE analytics using previous methodologies cannot help but get the bias results. This paper reviews and combines the basic knowledge for the new WCE analytics methodology using big data and M&S to overcome these problems of bias. Then this paper reviews the general overview of WCE, DM&S, and big data.