SATERA will propose and validate an integrity estimator for space-based ADS-B systems based on crosschecking positions reported in ADS-B messages with position estimations provided by space-based MLAT systems. To reach this goal, SATERA will apply a stepped approach starting by the definition of an initial OSED providing a high-level operational description at system level, identifying all the involved stakeholders, and detailing the CNS equipage of the fleet and the available air traffic services. Then, SATERA will adapt the system architecture described in the ED-142A for a composite ground-based surveillance system providing ADS-B and WAM surveillance to cope with the particularities of a space-based system. Next, the research team will develop theoretical models to assess and benchmark the proposed system architecture leading to a full list of functional requirements and interfaces description that will be captured in a Functional Description Document. SATERA will also adapt for a space-based system the performance requirements it has to meet according to the ED-142A for ENR-low/medium/high traffic densities. Afterwards, SATERA will develop a system performance prediction tool to compute the theoretical performance of a MLAT system whose receiving stations are onboard of a constellation of LEO small satellites. This tool will take into consideration all the error sources that can affect the MLAT system performance and will be used to update the initial OSED (if needed) and system architecture, and to select the most suitable constellation for validating the SATERA solution at TRL2 using an end-to-end system evaluation tool that will be developed by the research team as an evolution of the system performance prediction tool. The TRL2 validation will consist of several validation exercises addressing the provision of composite space-based ADS-B+MLAT surveillance in the EURSAM and NAT corridors for realistic traffic.

The SINAPSE project aims at proposing an intelligent and secured aeronautical datalink communications network architecture design based on the Software Defined Networking (SDN) architecture model augmented with Artificial Intelligence (AI) to predict and prevent safety services outages, to optimize available network resources and to implement cybersecurity functions protecting the network against digital attacks

ORCI will explore innovative AI-based solutions to help increase runway throughput using advanced automation support tools in the TMA domain. Specifically, the objective is to provide key information to Air Traffic Controllers in final approach sectors, to support informed decisions on when to issue vectoring instructions to aircraft for optimal spacing between consecutive arrivals during medium, high, very high-density and increasingly complex TMA airspace operations. To achieve this objective, the project will develop an AI model that is trained using radar surveillance data and ATC voice communications between pilots and controllers. During the project, Barcelona and Lisbon approach operations will be assessed. This will include interviews with ATCO experts from the respective ANSP partners, as well as in-depth analysis of local arrival characteristics (e.g. geometries, procedures, etc.). In addition, high amounts of radar surveillance and voice communications data will be collected and processed, to support and guide the training and testing of the AI models. The validation of the AI model will be supported by Human in the loop and Fast Time simulation techniques (using the RAMS Plus tool) to ensure that the performance of the AI model is evaluated in a realistic and controlled environment, and to get some initial human performance and safety related feedback. The successful implementation of the AI model is anticipated to optimize delivery of vectoring instructions, leading to enhanced capacity, efficiency, environmental performance, and overall improvements to arrival air traffic management that are consistent with SESAR performance targets. Additional benefits also extend to optimization of the runway throughput by reducing both ATC workload and the potential for human error. The expected solution could also be extended to incorporate the use of time-based separation for arrivals and digitally shared trajectory information coming from the flight-deck

Dynamic Airspace Configurations is at the core of the current and future European air traffic system. Enabling additional airspace capacity is a key factor to address the significant capacity challenges already faced in the recent past and to cope with the (expected) significant growth in air traffic, while maintaining safety, improving flight efficiency and reducing environmental impact. In line with the strategic goal, the main objective of SMARTS is delivering the right amount of capacity, at the right moment and with the maximum efficiency to better serve the air traffic demand. The aim is to make the airspace design and configuration process more efficient, taking full advantage of the airspace potential. Sectors and sector configurations should ensure that Air Traffic Controllers can handle the associated workload comfortably. To achieve this objective, SMARTS proposes to design sectors and sector configurations based on smart sectors. Smart in the sense that are aware of the environment (traffic and complexity prediction, capacity estimation, impact on other sectors), can act and adapt to improve the environment (create a sector design that produces a desired outcome in terms of workload/complexity), and can communicate with relevant actors (both local and network nodes). The smart sector is engendered by the design of basic volumes, and it is expected to provide the basis for an optimal distribution of workload, tailored around specific safety and operational requirements including complexity. As a by-product, the application of cost-efficient capacity actions allows a more accurate DCB planning in the early INAP phases thus reducing the number of required demand measures.

Communication, Navigation and Surveillance (CNS) systems are key in the provision of safe and efficient traffic management for air traffic. These systems have traditionally been ground-based and generally installed on mountain tops or at airports. Performance of these ground-based systems is limited by topography and availability of land. “New Space” and its two pillars (increasing availability and competition in the launch market increasing number of Low Earth Orbit satellites) is dropping the price of new constellations opening up for new and more cost efficient solutions in the provision of new services models. This is the case for global and seamless CNS services to be used in ATM. With requirements for Air Traffic to increase capacity and safety in the years to come, new solutions need to be deployed to ensure the correct management of Air traffic. The use of space-based infrastructure is a necessary step towards the provision of Air Traffic Services in remote areas or big sectors where they are not available today due to geographical constrains of terrestrial based systems. In this sense solutions towards the improvement of efficiency, safety and capacity of aviation, where Reduced Minima Separations in remote Airspace based on Satellite VHF Voice and Data Communications systems propose the answer. Other satellite-based technologies cannot provide a complete and integrated solution in terms of performances necessary to reduce separation. The objective of VLD2 - VOICE is to demonstrate that with the use of Satellite based VHF systems providing Voice and Datalink ATS traffic in remote airspace can be handled as in a contintenal, and current separation can be reduced non compromising safety. In addition we will perform some cross border operations between adjacent FIR belonging to different countries. Demonstration will cover operations in CANARIAS and SAL FIRs where ATCOs communcating in real time with Aircrafts at distances bigger than 1500km.