Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - CLASS (CLear Air Situation for uaS: Maturing ground based technologies for a real-time Unmanned Aerial System Traffic Management System (UTMS) to monitor and separate Unmanned Aerial System (UAS) traffic)

Teaser

The emerging traffic of drones is twofold. On one hand, drones offer a great opportunity for the industry, including agriculture and a large range of innovative businesses. On the other hand, drone traffic could be perceived as a threat, both physically to aircraft, people and...

Summary

The emerging traffic of drones is twofold. On one hand, drones offer a great opportunity for the industry, including agriculture and a large range of innovative businesses. On the other hand, drone traffic could be perceived as a threat, both physically to aircraft, people and properties on the ground as well as digitally with regards to privacy.

In order for drone business to thrive, these threats need to be mitigated. Together with the other SESAR Exploratory Research projects, CLASS aims at exploring the tools and services needed to safely integrate drones into the airspace, among the existing airspace users.
This set of services is called U-space and it aims at opening a fair and safe access to the airspace for all air-users.

CLASS aims to help define and constrain what U-space services are.

More specifically, CLASS focuses on drone tracking, including data fusion, traffic monitoring and tactical deconfliction.

Drone tracking is based on two complementary systems: a cooperative tracker and a non-cooperative tracker. A cooperative tracker is a dedicated electronic device which broadcasts its position. A non-cooperative tracker is a radar which can track targets as small as drones (and even small birds!). Of course, the radar detects the cooperative drones too. This is why data fusion techniques need to be investigated to fuse the two plots, combining the data from the cooperative tracker and the radar corresponding to the same object into one single plot.

Tracking cooperative drones (those that are carrying trackers) and non-cooperative drones (those that are not) opens the field of other services such as:
- protection of sensitive sites, such as airports. The combination of the radar and the embarked tracker will help sort out if a drone is authorised or not. This will improve safety and security.
- building the air situation. By locating all flying objects, the drone pilot or operator can avoid incoming aircraft.
- tactical deconfliction: automatic tools consider the drone\'s mission and current and past positions to check that no drone is in conflict. A conflict here means that they are likely to collide. The system suggests new trajectories consistent with traffic, so no new conflicts arise by solving the first one.
- monitoring. This service checks that the actual drone flights are consistent with the planned flights they were authorised for, and that no rules, like trespassing no drone-zones, are infringed.

Work performed

The project CLASS revolves around 5 main actions.

First of all, CLASS will define to how drones will be operated in the European sky. This is part of the Concept of Operations, shortened into CONOPS. As such, CLASS is strongly connected to all relevant stakeholders, not only from the drone community but from the air traffic management (ATM) community and the civil aviation authorities as well. The French School of Civil Aviation, ENAC, is in charge of maintaining the link between CLASS and the drone and ATM community. ENAC organised the first CLASS worskhop which aimed at gathering the requirements from the stakeholders. This workshop lead to the definition of 6 designed scenarios and key performance indicators (KPIs). These KPIs will help the CLASS partners to assess the efficiency and relevancy of the CLASS services in the frame of the U-space concept. CLASS is a part of the SESAR community . As such, CLASS gets inspiration from the latest updates of the ATM Master Plan. Finally, CLASS partners collaborate with other SESAR projects, mainly with the project CORUS which aims to define the European CONOPS.

Second, CLASS partners set up the systems to perform drone tracking. Airbus has in-house technology primarily devoted to the IoT business to drone tracking. This technology was adapted to create Drone-it!, the Drone Identifier and Tracker. Considering the defined scenarios, architecture and requirements have been proposed to track cooperative drones in the frame of live experiments. Aveillant optimised and trained the Gamekeeper, a holographic radar which can detect and track small drones. The CLASS scenarios were successfully flown with the ENAC\'s drones at the Aveillant facilites at Deenethorpe, UK. These flights created valuable data that were recorded for the Norwegian University of Science and Technology (NTNU) to tune the data fusion algorithm, which has been selected among several candidates.

Third, Unifly worked on the definition of the real-time air situation display and proposed an architecture that is able to cope with highly demanding requirements in terms of latency, real-time messaging and scalability. Unifly started to implement the interfaces between the Gamekeeper, Drone-it! and the real time display. Then, Airbus teams investigated deconfliction by adapting available algorithms from manned aviation. The traffic simulator and the conflict detection have been tuned to drone characteristics.

Fourth, a demonstrator, based on a drone simulator, has been deemed necessary to build to more easily enable the assessment of KPIs than field measurements.

Finally, the CLASS partners disseminate actions and results, not only towards the manned and unmanned communities (via events such as the World ATM Congress, Paris Air Show, ICAO) but also to the general public (webpage and press releases)

Final results

The next steps for CLASS are related to the definition of U-space services. CLASS is advanced enough to be able to really help in settling the definitions of the tracking, monitoring and deconfliction services. The live experiment that will take place in October will illustrate the tracking and monitoring from the drone detection up to the display through the data fusion, in real-time. Completing the demonstrator make it possible to provide useful data to the next generation of SESAR U-space projects.
Now that most of the pieces of CLASS are in place, the focus will be on dissemination and communication to share the CLASS results.

Website & more info

More info: http://class.aero.