Abstract This study presents an empirical analysis of drone defense strategies by evaluating human perceptual capabilities and firearm-based countermeasures against unmanned aerial vehicles (UAVs). The first experiment measured the visual and auditory recognition distances of drones, revealing that detection is strongly influenced by drone size and acoustic frequency characteristics, with visual recognition being more reliable than auditory perception. The second experiment assessed the effectiveness of various firearms operated by trained SWAT personnel, demonstrating limited hit probability, especially beyond 20–30 meters, and inconsistent drone neutralization even upon direct hits. Findings underscore the critical limitations of relying on human perception and conventional firearms in real-time drone threat scenarios, particularly in urban or civilian settings. The study concludes that current drone countermeasure strategies are misaligned with the evolving nature of UAV threats, especially those launched at close range with minimal reaction time. Future defense frameworks should prioritize automated detection and neutralization systems, develop non-lethal physical countermeasures, and integrate scenario-based response models to address emerging multidimensional threats effectively.
Lee et al. (2025) studied this question.