Comprehensive architecture for fixed-wing UAV-based search and rescue system: Real-time validation

Abstract

Search and Rescue (SAR) operations are essential and face challenges such as difficult terrain, limited resources, and time pressure. Fixed-wing UAVs offer a promising solution with aerial mobility and real-time data acquisition. However, existing SAR systems are often incomplete and static, lacking integration between high-level mission planning and low-level guidance systems and feedback mechanisms for dynamic adaptation. This paper proposes a novel SAR architecture that seamlessly integrates these elements. The core of our approach is the high-level subsystem, which generates a Probability Distribution Map (PDM) by combining diverse data sources such as target characteristics, UAV operational constraints, and environmental data from GIS. The PDM is updated in real-time based on sensor feedback, enabling dynamic trajectory and waypoint generation for optimal search efficiency. This dynamic, adaptive process is a key contribution to addressing critical gaps in current SAR systems. The proposed architecture undergoes comprehensive validation through two distinct methodologies. First, detailed scenario simulations are conducted using MATLAB®/Simulink to assess the framework’s theoretical performance. Subsequently, the framework is implemented and validated in a real-time Software In the Loop (SIL) architecture, utilizing a high-fidelity commercial flight simulator. This dual validation approach rigorously demonstrates the practical effectiveness and operational capabilities of the integrated SAR system.