Joint Virtual Battlespace (JVB) - Representing Network Centric Warfare with New and Legacy Simulations

摘要

Joint Virtual Battlespace (JVB) is a distributed simulation environment sponsored by the U.S. Army which is bringing legacy and developmental simulations together to represent future combat operations in support of SMART (Simulation & Modeling for Acquisition, Requirements and Training) analysis. Pivotal to the Army's emerging doctrine is the concept of Network Centric Warfare, but traditional simulations are often ill-equipped to model this concept. Legacy simulations are not able to represent the complex and rapidly reconfigurable network of information flow envisioned by developers of Army doctrine, nor are they able to address the conflicting requirements of high-fidelity communications and platform-level behavioral representation, and of theater-wide scope usually only available in aggregate-level simulations. JVB is attacking these problems by federating applicable legacy simulations in a distributed, service-oriented simulation environment, modifying their internal representations where possible, and bridging the remaining gaps in representation with a set of developmental models loosely called "The C3 Grid". Eagle and OTB form the core of JVB's legacy simulations. Extensive modifications have been made to enhance behavioral models of units and platforms. The Grid provides (along with many other functions), a dynamically reconfigurable, multidimensional grid of reporting, orders, and information flows. For example, fire missions (direct or indirect-fires) will not always come from the same command node. The C3 Grid provides the decision logic as well as the information topology for such orders. This paper discusses the approaches JVB is using to represent Network Centric Warfare using legacy and developmental simulations in a distributed, service-oriented environment. It addresses the problems of enhancing legacy models to represent network centric warfare, of linking entity-level and aggregate-level models, and of representing information flows in a high-fidelity, dynamically reconfigurable manner.