Since the late 18th century, unmanned aerial vehicles, more commonly known as drones, have undergone great development. Today, drones are a very important part of modern society, as they have revolutionized agriculture, photography, and logistics. However, their misuse poses serious risks to security, privacy, and public safety. Drone detection technologies have emerged as essential tools for identifying and managing unauthorized unmanned aerial vehicles to address these challenges effectively.

The most important aspect of drone detection is that it helps mitigate a number of threats, such as the intrusion of unauthorized drones into forbidden territories. These unauthorized drones may create dangerous situations within sensitive facilities such as airports, prisons, and military installations, and raise several privacy concerns when equipped with cameras that could intrude on personal and corporate spaces. Drones near crowded events also pose a safety concern, as criminals could equip them with dangerous weapons. Given these risks, reliable detection systems are in demand.

Drone detection technologies use numerous methods to identify drones. These include radio frequency detection, which monitors communication signals between drones and controllers, radar system mechanisms that track objects in the air using electromagnetic waves, acoustic sensors that pick up the unique sounds of drone motors, and optical systems that visually identify drones with cameras and AI. Hybrid systems that incorporate multiple approaches further improve the level of accuracy and reliability by fixing the limitations brought about by their individual use.

Applications for such systems are immense, from critical infrastructure protection to airport security to public event safety, even into military operations. Yet, such systems still grapple with high costs, a high number of false positives, and autonomous drone detection. The ongoing improvements in the technologies of artificial intelligence and machine learning continue to help raise the efficiency of drone detection systems to include the distinction of drones from other objects, the capability for flight path prediction, and adaptability to new drone models.

While the number of drones grows, so does the need to develop effective and efficient methods of detection. Future developments that ensure even greater accuracy through improved AI algorithms, for example, and collaborative detection networks will further enhance security. In other words, drone detection is not a follow-up to technological development but rather proactive–one that helps to ensure a safe and responsible incorporation of UAVs into society.

Information retrieved from Dedrone, MIT Technology Review, Power Engineering, and CNN.