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Live-Virtual-Constructive (LVC) simulations are complex systems comprising a combination of live (real people operating real equipment), virtual (real people operating simulated equipment or vice versa), and constructive (wholly simulated) entities. Nodes in the system support the simulation of one or more entities and are often geographically distributed to leverage unique assets (e.g., physical test range space or high-fidelity full motion simulators). Nodes are connected in a peer-to-peer fashion and communicate using protocols such as Distributed Interactive Simulation (DIS) [DIS Steering Committee 1998], the High Level Architecture (HLA) [Dahmann et al. 1997], or the Test and Training Enabling Network Architecture (TENA) [Powell and Noseworthy 2012]. Distributed LVC simulation promises a number of benefits for the test and evaluation (T&E) community, including reduced costs, access to simulations of limited availability assets, the ability to conduct large-scale multiservice test events, and recapitalization of existing simulation investments. Consequently, the Department of Defense (DoD) is increasingly turning to LVC simulation and virtual environments to support T&E events. LVC simulations have been used to test communications for unmanned aircraft systems [Parker et al. 2009], conduct cyber-security analysis [Van Leeuwen et al. 2010], and quantify radar measurement errors [Hodson et al. 2013]. Ensuring rigorous results for T&E events supported by LVC simulation requires addressing three fundamental data quality challenges: quantifying numerical errors due to weakly consistent nodes, assessing measurement accuracy with respect to tolerance requirements, and assessing measurement quality in the absence of absolute truth values.

Data Quality Challenges in Distributed Live-Virtual-Constructive Test Environments