For Air Operations Centers, there is a need to provide Commanders and their staff with real-time, up-to-the-second
information regarding Red-Force, Blue-Force, and neutral force status and positioning. These updates of the real-time
picture provide Command Staff with dynamic situational awareness of their operations while considering current and
future Courses of Action (COAs). A key shortfall in current capability is that intelligence, surveillance, and
reconnaissance (ISR) sensors, electronic intelligence, and human intelligence only provide a snapshot of the operational
world from "observable" inputs. While useful, this information only provides a subset of the entire real-time picture. To
provide this "missing" information, techniques are required to estimate the state of Red, Blue, and neutral force assets
and resources. One such technique for providing this "state" information is to utilize operationally focused simulation to
estimate the unobservable data. RAM Laboratories and the Air Force Research Laboratory's Information Systems
Research Branch are developing a Dynamic Situation Assessment and Prediction (DSAP) Software Framework that, in
part, utilizes embedded real-time simulation in this manner.
This paper examines enhancements made to the DSAP infrastructure's Multiple Replication Framework (MRF) and
reviews extensions made to provide estimated state information via calibrated real-time simulation. This paper also
provides an overview of the Effectiveness Metrics that can be used to evaluate plan effectiveness with respect to the realtime
inputs, simulated plan, and user objectives.
The Joint Synthetic Battlespace for Research and Development (JSB-RD) program is performing research and development in the areas of Modeling and Simulation (M&S), advanced visualization and analysis, and Decision Support. The goal of this work is to create a robust environment for use in ongoing research efforts in areas including Information Fusion, Effects Based Operations, and Predictive Battlespace Awareness. Present day mission level simulations suffer from overly simplistic, inaccurate communication link models that significantly overestimate available in-theater communications, a vital enabler of Command, Control and Communications (C3). Predictions based from such models can, and generally do, substantially differ from those encountered under actual battle conditions. In an effort to improve the accuracy and reliability of mission level simulation predictions, JSB-RD is adding detailed military link models into their core environment, along with the necessary logic to properly address C3 effects within the synthetic world. This paper chronicles these JSB-RD efforts to date.
This paper first presents a high level view of the JSB-RD project, followed by a detailed discussion of current efforts to enhance simulation predictions accuracy by integrating detailed military communications link models with existing military mission models.
A 1995 vision statement for Air Force Modeling and Simulation (M&S) highlighted the need for a Joint Synthetic Battlespace (JSB); an environment wherein warfighters could train and exercise on their real-world equipment while immersed in a realistic contingency or wartime environment. This paper describes our efforts to develop a Joint Synthetic Battlespace for Research and Development (JSB-RD), which will provide a realistic environment within which technologies being developed at AFRL's Information Directorate can be analyzed and tested. Where possible, this environment will attach to operational systems in order to provide military realism that will ultimately improve and shorten the tech transition process. This reconfigurable testbed will provide scalability and evolve over time building upon previous federations, attaching to other federations, while incorporating lessons learned along the way.
Joint Synthetic Battlespace for Decision Support (JSB-DS) is a developing set of concepts and an affiliated prototype environment with a goal of investigating the nature of decision support within a Command and Control (C2) context. To date, this investigation has focused on processing raw operational data into decision quality information and then presenting that information in a format that is useful and intuitive to a decision maker. The JSB-DS prototype was developed to support experimentation involving visual representation of, and interaction with, operational information. JSB-DS's prototype environment utilizes mission level battlefield simulations as a means to investigate decision and visualization aids with respect to situation awareness and reduction in decision timelines. These distributed simulations support dynamic re-tasking of Intelligence, Surveillance and Reconnaissance (ISR) and airborne strike assets within a Time Critical Target (TCT) prosecution vignette. The JSB-DS environment can serve as a basis for testing C2/TCT processes, procedures and training.
Developing models for simulation is an arduous task. After building a high fidelity model, computation time can be prohibitive for general testing due to processing at higher levels of resolution. One way to address this problem is to develop abstract representations of the models that only consider “key” variables or parameters. For identifying these “key” variables or parameters, it may be desirable to determine the sensitivity of certain variables with respect to model outputs or response. One way of calculating the sensitivity of variables requires the analysis of output variables using clustering techniques. The MRMAide technology (MRMAide stands for Mixed Resolution Modeling Aide) employs a sensitivity analysis as an enabling technology that allows the program to test the sensitivity of certain variables and analyze the correlation of coupled variables. Using this tool helps the developer analyze how a model can be abstracted so that it can be rewritten to reduce the number of calculations but keeping an acceptable level of accuracy. Distributions can then be fed into these variables rather than calculating their values at each step resulting in a lower fidelity, yet fairly accurate representation for given operating conditions.
The Air Force Hierarchy of Models, often referred to as the Great Pyramid, depicts the four disparate levels of resolution in which models are typically categorized. These levels range from an Engineering/Component level at the bottom, to Theater/Campaign level at the apex of the pyramid. Today, the landscape of simulations has evolved from uni-purpose, stove-piped simulations to those that provide a Joint Vision encompassing a much broader scope. Within the simulation community, there exists the desire for model reuse, particularly when it involves the reuse of validated legacy codes. Much effort has been put forth to integrate existing models into a federated system. Integrating models of similar resolution is difficult enough; yet, even more difficult is the more prevalent situation where models are represented at different levels of resolution. Often referred to as Mixed Resolution Modeling (or Multiresolution Modeling), it is arguably the most pressing problem facing the simulation research community today. This paper will describe an attempt to address the MRM problem by applying model abstraction techniques to reduce the complexity of a detailed model without sacrificing the essence of the model. This surrogate version of the detailed model will then be able to play within a more aggregate simulation environment. To demonstrate, JSAF (Joint Semi- Automated Forces) will be used to simulate the behavior of models at both the detailed and abstract levels. The results will be compared to demonstrate the impact and utility of model abstraction.
Proc. SPIE. 4026, Enabling Technology for Simulation Science IV
KEYWORDS: Target detection, Radar, Defense and security, Visual process modeling, Data modeling, Analytical research, Modeling and simulation, Performance modeling, Systems modeling, Distributed interactive simulations
The widely-used Air Force hierarchy of models and simulations is generally depicted as a four-level pyramid; ranging from Engineering/Component Level up to Theater/Campaign Level. While it does present a concise picture of the scope of military models and simulations, it gives the impression that there is a smooth and natural transition from one level to the next. That is not the case. In fact, there is a great variance in degree of complexity from one level to the next. This paper looks at the state- of-practice in modeling and simulation in the context of this hierarchy; and in particular, at traditional and revolutionary techniques involving inter-level relationships.