Authors :
M. Nageshwarappa; Het Pandya; Dr. Mansi Shanishwara
Volume/Issue :
Volume 11 - 2026, Issue 4 - April
Google Scholar :
https://tinyurl.com/4hh7rb5y
Scribd :
https://tinyurl.com/3fer7k56
DOI :
https://doi.org/10.38124/ijisrt/26apr1017
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, are increasingly utilized in industries such
as logistics, agriculture, surveillance, and security. However, the rapid growth of UAV deployment has introduced serious
threats to civil aviation and airport operations. Unauthorized drones can disrupt flight schedules, conduct illegal
surveillance, and transport hazardous payloads. Traditional airport security systems are primarily designed for groundbased threats and often fail to detect low-altitude aerial intrusions. This research proposes an integrated airport security
framework combining radar systems, UAV surveillance, sensor networks, and centralized monitoring infrastructure. The
system enhances real-time detection, improves response efficiency, and reduces false alarms. A case study of Rajiv Gandhi
International Airport demonstrates that UAV-assisted surveillance significantly strengthens airport security systems.
Keywords :
Drone Security, UAV Surveillance, Airport Security, Smart Surveillance, Aviation Safety.
References :
- International Civil Aviation Organization, "Manual on Remotely Piloted Aircraft Systems (RPAS)," ICAO Doc 10019, 2015.
- Federal Aviation Administration, "Integration of Civil Unmanned Aircraft Systems (UAS) in the National Airspace System Roadmap," FAA, 2020.
- European Union Aviation Safety Agency, "Easy Access Rules for Unmanned Aircraft Systems," EASA, 2021.
- International Air Transport Association, "Guidance on Unmanned Aircraft Systems," IATA, 2019.
- Directorate General of Civil Aviation, "Civil Aviation Requirements for Remotely Piloted Aircraft Systems," DGCA India, 2018.
- Airports Authority of India, "Airport Security Guidelines," AAI, 2020.
- ISO, "ISO 21384-3: Unmanned Aircraft Systems—Operational Procedures," ISO, 2019.
- J. K. Kuchar and L. C. Yang, "A Review of Conflict Detection and Resolution Modeling Methods," IEEE Trans. Intelligent Transportation Systems, vol. 1, no. 4, pp. 179–189, 2000. DOI: 10.1109/6979.898217
- A. V. Savkin and H. Huang, "A Survey of Security Issues in UAV Communication Networks," IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2801–2835, 2019. DOI: 10.1109/COMST.2019.2902862
- M. Ritchie, F. Fioranelli, and H. Griffiths, "Micro-Doppler Radar Signatures of Drones," IEEE Radar Conference, 2017. DOI: 10.1109/RADAR.2017.7944296
- F. Nex and F. Remondino, "UAV for 3D Mapping Applications: A Review," Applied Geomatics, vol. 6, pp. 1–15, 2014. DOI: 10.1007/s12518-013-0120-x
- I. Colomina and P. Molina, "Unmanned Aerial Systems for Photogrammetry and Remote Sensing," ISPRS Journal, vol. 92, pp. 79–97, 2014. DOI: 10.1016/j.isprsjprs.2014.02.013
- H. Shakhatreh et al., "Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges," IEEE Access, vol. 7, pp. 48572–48634, 2019. DOI: 10.1109/ACCESS.2019.2909530
- Y. Zeng, R. Zhang, and T. J. Lim, "Wireless Communications with UAVs: Opportunities and Challenges," IEEE Communications Magazine, vol. 54, no. 5, pp. 36–42, 2016. DOI: 10.1109/MCOM.2016.7470933
- Q. Wu et al., "Machine Learning for UAV Detection and Classification," IEEE Transactions on Neural Networks and Learning Systems, 2020. DOI: 10.1109/TNNLS.2020.2972608
- K. P. Valavanis and G. J. Vachtsevanos, "Handbook of Unmanned Aerial Vehicles," Springer, 2015. DOI: 10.1007/978-90-481-9707-1
- M. Mozaffari et al., "A Tutorial on UAVs for Wireless Networks," IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2334–2360, 2019. DOI: 10.1109/COMST.2019.2902862
- S. Hayat, E. Yanmaz, and R. Muzaffar, "Survey on Unmanned Aerial Vehicle Networks," Journal of Network and Computer Applications, vol. 39, pp. 206–220, 2016. DOI: 10.1016/j.jnca.2013.10.015
- L. Gupta, R. Jain, and G. Vaszkun, "Survey of Important Issues in UAV Communication Networks," IEEE Communications Surveys & Tutorials, vol. 18, no. 2, pp. 1123–1152, 2016. DOI: 10.1109/COMST.2015.2495297
- P. Doherty and P. Rudol, "A UAV Search and Rescue Scenario with Human Body Detection and Geolocalization," AI Magazine, vol. 28, no. 1, pp. 55–66, 2007. DOI: 10.1609/aimag.v28i1.2035
- M. I. Skolnik, "Introduction to Radar Systems," McGraw-Hill, 2001.
- M. Richards, "Fundamentals of Radar Signal Processing," McGraw-Hill, 2014.
- F. Fioranelli et al., "Classification of Drones Using Radar Micro-Doppler Signatures," Electronics Letters, vol. 51, no. 22, pp. 1813–1815, 2015. DOI: 10.1049/el.2015.2617
- J. Molina-Garcia et al., "Drone Detection and Classification Using Radar," IEEE Sensors Journal, vol. 20, no. 21, pp. 12805–12815, 2020. DOI: 10.1109/JSEN.2020.3005643
- A. Al-Sa’d et al., "RF-Based Drone Detection and Classification Using Machine Learning," IEEE Access, vol. 7, pp. 109834–109845, 2019. DOI: 10.1109/ACCESS.2019.2933242
- B. Kim et al., "Deep Learning-Based Drone Detection Using RF Signals," IEEE Access, vol. 8, pp. 186927–186940, 2020. DOI: 10.1109/ACCESS.2020.3029911
- X. Liu et al., "Edge Computing for UAV Networks," Future Generation Computer Systems, vol. 102, pp. 324–336, 2020. DOI: 10.1016/j.future.2019.08.048
- M. Zhang et al., "AI-Based UAV Detection System," Journal of Big Data, vol. 9, 2022. DOI: 10.1186/s40537-022-00580-0
- P. Mell and T. Grance, "The NIST Definition of Cloud Computing," NIST, 2011. DOI: 10.6028/NIST.SP.800-145
- S. Sicari et al., "Security, Privacy and Trust in IoT," Computer Networks, vol. 76, pp. 146–16
Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, are increasingly utilized in industries such
as logistics, agriculture, surveillance, and security. However, the rapid growth of UAV deployment has introduced serious
threats to civil aviation and airport operations. Unauthorized drones can disrupt flight schedules, conduct illegal
surveillance, and transport hazardous payloads. Traditional airport security systems are primarily designed for groundbased threats and often fail to detect low-altitude aerial intrusions. This research proposes an integrated airport security
framework combining radar systems, UAV surveillance, sensor networks, and centralized monitoring infrastructure. The
system enhances real-time detection, improves response efficiency, and reduces false alarms. A case study of Rajiv Gandhi
International Airport demonstrates that UAV-assisted surveillance significantly strengthens airport security systems.
Keywords :
Drone Security, UAV Surveillance, Airport Security, Smart Surveillance, Aviation Safety.