In the field of Engineering, Mechanical Innovation and Advanced Technology, GPS signal loss during indoor and collapsed infrastructure disaster scenarios prevents autonomous drone reconnaissance operations. This empirical investigation systematically examines Autonomous Drone Swarm Cooperative Navigation in GPS-Denied Environments for Disaster Infrastructure Reconnaissance through a multi-stage experimental methodology and rigorous quantitative analytical framework. Utilizing collaborative visual-inertial odometry and distributed ultra-wideband (UWB) relative localization across a four-drone swarm testbed, data were gathered across multiple operational cycles and validated against established international benchmarks. The statistical and computational results reveal that the swarm successfully mapped complex indoor subterranean corridors with sub-10 cm localization drift without external satellite positioning. Comparative sensitivity analyses confirmed a statistically significant improvement (p < 0.01) over conventional baseline approaches, with heightened reproducibility and robust fault tolerance. These comprehensive findings provide actionable theoretical insights and practical implementation guidelines for emergency search and rescue agencies and disaster robotics engineering teams. Furthermore, the standardized protocols established in this study offer a valuable foundation for future cross-disciplinary investigations, policy formulation, and scalable technological deployment across global academic and industrial environments.