A COMPARATIVE STUDY OF SOFTWARE-DEFINED RADIO (SDR) AND SMART ACOUSTIC SENSOR PERFORMANCE FOR UAV DETECTION

Abstract

Unmanned aerial vehicles (UAVs) pose significant security challenges, especially in sensitive areas such as government buildings, schools, kindergartens, and borders. Effective detection and identification of UAVs are critical to protect sensitive areas from unauthorized access or hostile use. In terms of the ability to effectively detect the activity of suspected UAVs in these critical areas, there are two frequency-based detection technologies: acoustic sensors and program-defined radio (SDR). This study presents a comparative analysis of these technologies and evaluates their effectiveness in UAV identification. By analyzing UAV acoustic signatures and radio frequency (RF) emissions, we attempted to evaluate the strengths, limitations, and practical applications of each system. Our findings indicate that although both technologies are effective, the choice between them depends on environmental conditions, UAV characteristics, and specific use cases. Furthermore, we attempted to analyze their effective performance sides to combine both for reliable recognition.