Keywords

Virtual Reality Training, Counter-Unmanned Aircraft Systems (C-UAS), Multi-Target Engagement, Modular Simulation Framework, Immersive Military Training, Unity3D Simulation

Subject Categories

Human Factors Psychology | Military and Veterans Studies

Abstract

Unmanned aerial systems (UAS), commonly referred to as drones, have become a rapidly growing challenge in modern military operations. In particular, the increasing use of small, agile, and low-cost systems—such as first-person-view (FPV) drones and coordinated multi-drone deployments—places high cognitive demands on operators, requiring rapid target detection, prioritization, and decision-making under time pressure.

Existing training approaches either rely on costly and logistically constrained live exercises or focus primarily on isolated piloting and shooting tasks, without sufficiently addressing these cognitive demands. At the same time, advances in commercial off-the-shelf (COTS) virtual reality (VR) hardware enable scalable, flexible, and repeatable training environments. This thesis presents the VR Drone Training (VRDT) framework. It is designed as a modular Drone Awareness and Situational Trainer for multi-target drone defense scenarios under time pressure. Implemented in Unity and deployed on standalone Meta Quest hardware, the system provides a structured training progression across three modes with increasing cognitive and operational complexity.

An exploratory user study with military participants evaluated usability, perceived workload, perceived realism, and training value. The results suggest that the system is highly usable and provides a coherent progression of cognitive demands across training modes. While physical realism is deliberately abstracted, participants reported high engagement and identified the system as a valuable complement to existing training approaches, though they also noted specific areas for refinement, particularly in drone movement complexity and weapon interaction.

These findings indicate that COTS-based VR systems can provide a promising foundation for scalable and cognitively focused counter-UAS training.

Completion Date

2026

Semester

Summer

Committee Chair

Bruder, Gerd

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

School of Modeling, Simulation and Training

Format

PDF

Document Type

Thesis

Language

English

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