OptoFence II

Project goals

Development of a fast telescopesystem for UAV-Tracking
Kamera based control with image stabilisation
Realtime image and determination of trajectories

Description

Drones and other types of unmanned aerial vehicles (UAVs) have gained massive popularity not only in the professional but also in the private sector in recent years. Incidents such as the closure of London’s Gatwick Airport due to a drone sighting demonstrate that advances in UAV technology pose a threat to public safety. The early identification of incoming UAVs is of the highest priority for situational assessment.
Commercial drone detection systems use a multispectral approach for object detection and identification. For this purpose, the interaction of different sensors is used to be able to recognize and identify objects. The figure below shows an example where an object at a distance of 5 to 10 km is detected using radar. The problem, however, is that it is difficult to differentiate between a UAV and, for example, a bird. Optical sensors are used for this, which can clearly classify the object based on a recorded camera image. The operational distance of this optical component is currently limited to one to two kilometers, which only allows short reaction times in the event of a threat.

Illustration of a commercial drone detection system. State of the art technology provides in worst case only 15s for optical detection, identification and situation assessment.

OptoFence II aims to develop a telescope-based optical platform to enable a larger identification area, which significantly increases situational awareness. The combination of a precise and fast mount, a high-quality telescope, a camera system and advanced methods of control systems and computer vision creates a versatile platform for the optical detection, tracking and identification of UAVs.

Left: Overview of OptoFence II System concept. Right: Example image captured through telescope.

The basic concept is shown in Figure 2 left. A suitable pair of telescope and camera provides a high-resolution image. In the next step, this is analyzed using modern deep learning algorithms in order to extract the position of the UAV in the image. The data obtained serves as input for advanced control engineering controllers in order to let the telescope precisely follow the trajectory of the object.

OptoFence II System implementation

Use case

UAV reconnaissance

Related Publications

D. Ojdanic, A. Sinn, C. Schwaer, and G. Schitter, UAV Detection and Tracking with a Robotic Telescope System, in Proceedings of the Advanced Intelligent Mechatronics Conference 2021, 2021.
[BibTex]

@inproceedings{TUW-299533,
author = {Ojdanic, Denis and Sinn, Andreas and Schwaer, Christian and Schitter, Georg},
title = {UAV Detection and Tracking with a Robotic Telescope System},
booktitle = {Proceedings of the Advanced Intelligent Mechatronics Conference 2021},
year = {2021},
note = {Posterpr{\"a}sentation: 2021 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Delft, Netherlands; 2021-07-12 -- 2021-07-16}
}