AutonomouS SYstem for Decoying using Uav Swarms – ASSYDUS
ASSYDUS - AutonomouS SYstem for Decoying using UAV Swarms – aims at radar decoy by autonomous swarms of Unmanned Aerial Vehicles.
Creation of an autonomous aerial drone swarm to decoy a radar.<br /><br />Project developped by Thales and University of Bordeaux
Main issues raised & general objectives
Assess small aerial drones ability to increase their Radar Cross Section artificially. Such collaborative platforms, with embedded artificial intelligence, can autonomously fulfil decoying missions.
- radar signal processing
- aerial drone precise location tracking
- collaboration among the drones
- increase one and several drones visibility, by a radar
- Autonomous computation of a flight configuration
- Dynamic swarm reconfiguration thanks to drones collaboration and precise location tracking.
Examples of civil & military applications:
- Conduct missions in hard to reach and constrained environment (urban disaster areas, forests);
- Maneuver in hostile area before manned vehicle intervention.
Robustness, fault tolerance, self-healing, survivability, resilience
and native resilience of a swarm of drone, Serge Chaumette, Lucas Monlezun, ccs2023.org
As part of the exploration of the concepts of artificial intelligence and robotics in future combat systems, a concept was developed (and validated by operational staff) on the use of drones to deceive ground-to-air defense systems, or opposing combat aircrafts. The originality of the principle adopted is to position the drones of a swarm autonomously in order to obtain a Radar Cross Section (RCS), measured by the radar of the ground-to-air system, which is equivalent to that of a combat aircraft and to set up drones (a swarm) management so as to lure the radar which would measure the target's Doppler. The aim of the ASSYDUS project is the theoretical study, simulation and laboratory prototyping of such an approach based on the expertise of Thales DMS and LaBRI, the computer science research laboratory of the University of Bordeaux, in the fields of radars, drones, swarms of autonomous drones artificial/embedded intelligence.
Project coordination
Gilles GUERRINI (THALES DMS FRANCE SAS)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partner
TDMS THALES DMS FRANCE SAS
LaBRI Laboratoire Bordelais de Recherche en Informatique
Help of the ANR 232,314 euros
Beginning and duration of the scientific project:
- 24 Months
