Aladdín

The objective of this project is to develop an advanced platform to detect, locate, classify, and neutralize light and suspicious drones over restricted areas. It aims to provide tools for operational support, including investigations and training. ALADDIN will also assess relevant technologies, threat trends, regulations, and other issues related to the social, ethical, and legal environment in order to provide new insights to Security Forces as well as infrastructure designers and builders.

Topic/ SEC

SEC-12-FCT-2016.   Detection and neutralization of suspicious light unmanned aircraft flying over restricted areas.
Duration 36 months.
MMP Units International Relations Section.
Participant countries

Spain, France, Greece, Germany, Poland, Belgium, Italy, United Kingdom, and Portugal.
Summary

The ALADDIN Project will study, design, develop, and evaluate a system against drones, offering a comprehensive solution to the growing threat posed by Unmanned Aerial Vehicles (UAVs) or "drones". It will be based on cutting-edge technology and pioneering research in state-of-the-art technologies.

ALADDIN will follow a holistic and user-centred methodology, involving different police forces, operators of critical infrastructure, and an external panel of experts to ensure diversity of technological users, as each of them faces different types of threats and operates within different regulatory frameworks.

This diversity is crucial in shaping the specifications of EU-scale systems and innovative training programs that will be conducted to share acquired knowledge and increase awareness.

ALADDIN will comprise a set of new, customized, innovative, and unique technologies, as well as established sensors and standards used for the detection and localization of drones, such as:

  1. Connected 2D/3D radars.
  2. Innovative panoramic, thermal and optronic.
  3. Customized acoustic sensors.

All of these will be fused through new deep learning techniques in order to provide excellent detection accuracy.

Finally, ALADDIN will study and offer a set of neutralization technologies operated through an advanced command and control system that will achieve high detection and classification accuracy within a wide range, merging data acquired from all sensors through advanced deep learning techniques. Operator efficiency will be enhanced through a novel mixed reality interface with 3D cartographic and situational elements, complemented by support for investigation and training operations.
Subir Bajar