A Review of AI-Enabled UAV-Based Systems for Defense Applications

Abstract

Unmanned aerial vehicles have become indispensable components of modern defense systems by conducting Intelligence, Surveillance, and Reconnaissance (ISR) missions to collect critical operational information through onboard sensing technologies, supporting secure communication and information sharing among distributed military assets, and enhancing battlefield situational awareness through real-time sensing and data fusion. In addition, UAVs are increasingly capable of executing a wide range of defense missions, including target search and tracking, electronic warfare, search-and-rescue, and combat support. The integration of AI into UAV-based systems has the potential to enhance these operational capabilities by enabling intelligent perception, autonomous decision-making, adaptive mission planning, autonomous navigation, resilient communications, and cooperative multi-UAV coordination, thereby enabling the autonomous and collaborative execution of complex defense missions. This paper presents an up-to-date review of AI-enabled UAV-based defense systems, focusing on major operational domains including autonomous air combat and cooperative UAV operations, path planning and autonomous navigation, target tracking/detection/classification, cybersecurity, electronic warfare protection, and resilient UAV operation. In addition to surveying the recent literature, this paper provides an integrated system architecture, a functional classification framework, and an analysis of the AI paradigms enabling next-generation UAV-based defense systems. Furthermore, this review synthesizes the key technological trends, lessons learned, and cross-domain research challenges identified across the reviewed studies, providing a unified perspective on the current state of the field. Finally, this paper highlights promising future research directions for resilient, scalable, secure, and intelligent next-generation AI-enabled UAV-based defense systems.