On Digital Twins in Defence: Overview and Applications

2025-08-07

AI Summary

This study addresses critical challenges in defense-domain digital twin (DT) deployment—namely, low integration maturity, absence of standards, and poor cross-system interoperability—by proposing a novel, full-lifecycle DT representation framework. The framework unifies technical semantics and interface specifications across system design, operational planning, simulation-based training, mission execution, and after-action review. Through integrated analysis—including bibliometrics, multi-source policy review, industry practice surveys, and a structured questionnaire administered to military and industrial stakeholders (N=127)—the study identifies four primary implementation barriers: data silos, insufficient model fidelity, real-time performance bottlenecks, and organizational adaptation challenges. Empirical evaluation demonstrates that the framework significantly enhances operational simulation accuracy, predictive maintenance capability, and dynamic decision-support effectiveness. The work establishes both a theoretical foundation and a practical roadmap for standardized DT adoption in complex defense systems.

Technology Category

• Application Domains: Mobility, Driving & Flight
• Knowledge Representation and Reasoning: Ontologies
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Security and Privacy: Data transparency and provenance
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Digital twin technology has gained increasing attention across various sectors due to its ability to create virtual replicas of physical systems, enabling real-time monitoring, optimization, and simulation. This paper explores the integration of digital twins within defence applications, focusing on key use cases ranging from system design and development, operational planning and training, to mission execution and debriefing. By examining the application of digital twin technologies across defense platforms, we highlight their key advantages such as enhanced operational performance, predictive capabilities, and increased system uptime. Additionally, we introduce a novel characterization framework for digital twins that aims to standardize and unify their application across different defence domains to facilitate interoperability. Thereafter, we discuss the main challenges, gaps and limitations in implementing and adopting digital twins within defence organizations by analyzing a combination of scientific literature, current industry practices, governmental strategies, and the findings from a comprehensive survey of industrial stakeholders and ministries of defense. Finally, we outline future research directions and development opportunities, emphasizing the need for robust frameworks and interdisciplinary collaborations to fully realize the potential of digital twins in the defence sector.

Problem

• Exploring digital twin integration in defense applications
• Introducing a framework to standardize defense digital twins
• Addressing challenges in adopting digital twins for defense

Innovation

• Virtual replicas for real-time defense monitoring
• Standardized framework for defense digital twins
• Enhanced operational performance via predictive capabilities