Executive Summary
This systematic review examines the development of AI-enhanced simulation for air and missile defense operations, focusing on modeling architectures, decision support, and adaptive analysis. It synthesizes conventional approaches with AI techniques, addressing challenges like data quality, model fidelity, and interoperability. The review proposes a hybrid, data-centric, adaptive, interoperable, and human-centered simulation ecosystem for future defense applications.
Why It Matters
This document is crucial for defense analysts as it outlines how AI-enhanced simulation can revolutionize air and missile defense operations, improving decision-making, training, and system development in complex threat environments.
Key Takeaways
- AI-enhanced simulation integrates conventional modeling with machine learning, deep learning, and reinforcement learning to create adaptive and intelligent defense systems.
- Key challenges include data quality, model fidelity, interoperability, and the need for explainable AI and continuous validation in high-stakes defense applications.
- The future of air and missile defense simulation will be hybrid, combining physics-based models with AI, digital twins, and human-centered design for a robust ecosystem.
Strategic Relevance
The integration of AI into air and missile defense simulation is strategically vital for developing advanced capabilities, enhancing operational readiness, and improving decision-making speed and accuracy against evolving aerial threats. It supports the design, testing, and deployment of next-generation defense systems.