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The research conducted at ENSTA Bretagne by this Lab-STICC team is primarily aimed at representing and understanding certain phenomena resulting from the interaction of electromagnetic waves with the environment.
The team is seeking to further integrate innovative concepts and artificial intelligence into systems for the acquisition and processing of observations from radar (whether airborne or satellites) or GPS-type geolocation systems.
These algorithms use no-threshold measures, in scenarios where conventional approaches fail, owing to low signal-to-noise ratios (SNR) or restrictive environments.
An original algorithm has been developed in partnership with Diades Marine, as part of the ADEME e-PANEMA project (e-Positioning and Navigational Aid in the Marine Environment) and won the IEEE Antennas and Propagation Society award in 2019.
It was developed by using particle filters for the detecting and tracking of targets; its performances were assessed using actual radar data.
DOREDO is a system for detecting and locating obstacles and objects, which can be embedded on medium-endurance drones, warning of any potential collision route with other aircraft (of the light aircraft, helicopter or recreational drone type for example).
The system allows for secure flight, with comparable characteristics to current airliners thanks to the removal of such technological hurdles as miniaturization and robustness regarding air or land clutter.
>> DOREDO is a first step towards the flight of medium-endurance drones within non-segregated airspace.
Funded by: DGA. Partners: CESTIM, CNAM Paris
Scalable deep-learning techniques for the detection and recognition of targets from heterogeneous data.
Funded by: DGA, AID, I2R
Characterizing the atmosphere and sea surface interactions for the deployment of offshore wind in the Gulf of Lion.
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