Due to the rapidly increasing number of leisure drones operated everywhere, different accidental and deliberate incidents happen and even are becoming severe when happened in a critical area, like, for example, airports, ports, events in city areas, etc…

As it is possible to see from the table below, some examples of incidents in different domains have demonstrated the need for an effective anti-drone solution in the Homeland market:

• Airports: Between 19 and 21 December 2018, hundreds of flights were cancelled at Gatwick Airport near London, England, following reports of drone sightings close to the runway (more information can be found here).
• Buildings, Monuments and Events in Cities: On the 2nd of August 2021, a DJI Air 2S drone flew into a skyscraper, located in New York City's World Trade Center complex, became wedged between window panels located outside building (more information can be found here).
• Ports: On June 4, 2021, a man lost control of the drone he was flying over Hudson Yards and it first crashed into a Vessel before it plummeted into the Soul Cycle tent, luckily without injurie (more information can be found here).
• Important Sportive Events: On June 11th 2016, a woman participating to a running race was hit on her head by a DJI Phantom 3 drone, weighing 2.7 pounds that was trying to film, without permissions, the sportive event (more information can be found here).

The presence of rogue drones can be detected by several different methods (e.g. RF scanning, Electro-optical and Infrared sensors, acoustic sensors, radar, …) but each of them presents different drawbacks that do not fulfill the user needs in terms of continuous and available security.

The MEDuSA Solution, based on forward scattering detection, applies innovative algorithms to the carrier phase measurements of the GNSS signals to detect phase anomalies due to the passage of the drone. These core algorithms are applied on all the deployed GNSS sensors’ mesh and, the detection results are then sent to the Control Centre where innovative techniques (e.g. Machine Learning/Kalman Filters to be trade-off during the project) are applied to the detection information to estimate the drone trajectory. The use of Galileo is a fundamental element of the MEDuSA Solution thanks both to the highly stable signals (due to the Galileo on-board atomic clocks) and to its added-value OSNMA Service.