The Drone Hunting System

The rise in drone usage has brought about various challenges and concerns regarding safety and security. Drones are interfering at civilian airports and other critical infrastructure and the need for an anti-drone or drone hunting system has become more urgent. The rising fears of using modified consumer drones for terrorist attacks and anonymous threats to factories, stadiums, and government institutions have also made it crucial to develop a security system against such threats.

As a part of development for a valued client, the Fly4Future team has created software solution that addresses these concerns by providing a reliable and efficient means of detecting and neutralizing unauthorized drones.

Thanks to the opportunity to work on an autonomous anti-drone solution for one of our clients, Fly4Future has made significant strides in the development of this particular area of defense application. Through the implementation of complex control and computer vision techniques, this innovative technology is capable of fully autonomous drone hunting. By leveraging advanced control algorithms and sophisticated computer vision capabilities, Fly4Future’s autonomous anti-drone solution can effectively identify and track drones in real time. This enables swift response measures to be taken to mitigate potential threats posed by these unmanned aerial vehicles.

The integration of complex control techniques ensures precise maneuvering and navigation capabilities for the anti-drone system. Additionally, the utilization of cutting-edge computer vision techniques allows for the accurate identification of drones amidst complex environments. The Fly4Future system distinguishes a drone from other objects (such as birds) and alerts an operation center. The innovative approach sets a new standard for addressing safety concerns associated with drones while maintaining airspace security.

A 3D multi-target tracking algorithm filters the output of the detection algorithm to reduce false positives. It also preserves the detection’s temporal consistency and predicts the drones’ positions (e.g. to compensate for camera and processing delays).

The drone hunter uses onboard neural networks and artificial intelligence. Thanks to this, it is able to detect, classify, track, and predict the movement of the intruding drone. As a result, the drone hunting system is capable of planning a neutralizing maneuver.

The drone hunter hunts the enemy drones by catching them with a deployed net.  An onboard net gun launches and casts the net over a large space, thereby increasing the likelihood of successful intervention when compared to other solutions. The shot is triggered autonomously by an onboard computer, although confirmation from an operator can also precede the trigger. However, security-critical applications can use the system solely in autonomous mode without any operator to speed up the neutralizing maneuver.

After deployment, the net remains connected to the drone hunter via a rope, preventing the caught drone from being dropped. It can then be safely transported to a specific location for further investigation.