SPIRIT-UCS aims to enable safe, scalable, and efficient drone operations in low-level airspace by defining risk-based performance requirements for U-space services and surveillance systems. The project focuses on modelling the operational risk of drone flights, developing safety criteria tailored to specific environments, and validating innovative positioning and conflict detection solutions based on 5G technologies and simulation platforms. Through a combination of theoretical modelling, real-world testing, and simulation, SPIRIT-UCS contributes to the future integration of drones into complex airspace environments..

Objectives

The main objective of SPIRIT-UCS is to define and validate a comprehensive safety framework for UAS operations in U-space, grounded on a risk-based approach that adapts to the complexity and criticality of the operational environment. Specifically, the project aims to:

• Develop a structured collision risk model based on accident precursors and mitigation barriers, enabling the quantification of safety levels in diverse scenarios.
• Define standardized Operational Environments (OEs) and associate each with specific Target Levels of Safety (TLS), allowing differentiated safety requirements.
• Derive Safety, Performance and Interoperability Requirements (SPIRs) for surveillance and communication systems, aligned with regulatory and operational needs.
• Design and implement a surveillance system based on 5G multilateration (MLAT) using PRS signals and TDOA techniques.
• Build an integrated Software-in-the-Loop (SITL) simulation platform to emulate realistic drone operations and environmental conditions.
• Develop and test a multi-USSP environment with centralized strategic and tactical conflict detection services.

Concept

SPIRIT-UCS is built on the premise that ensuring the safe integration of drones into low-level airspace requires dynamic, risk-aware performance requirements tailored to the specific characteristics of each operational scenario. Instead of applying uniform safety margins, the project adopts a scalable and context-sensitive approach, where separation criteria and system requirements adapt to variables such as population density, airspace structure, traffic complexity, and available CNS services.

At the core of the project is a risk model structured around the Accident/Incident Model (AIM), which maps how operational hazards evolve into collisions and identifies where safety barriers can effectively mitigate risk. This model serves as the foundation for deriving Safety, Performance and Interoperability Requirements (SPIRs), ensuring that surveillance and communication systems meet the demands of each operational environment.

SPIRIT-UCS combines analytical modelling, software simulation, and real-world testing to validate its approach. It explores how 5G-based multilateration (MLAT) systems can support accurate drone positioning, and how services like strategic conflict detection can be implemented in multi-USSP architectures using spatial data structures (e.g., octree). This integration of risk analysis, technical performance, and service design enables a coherent framework for future U-space operations.

Methodology

SPIRIT-UCS follows a structured, multi-stage process that integrates risk modelling, requirements derivation, technological development, and validation. The methodology is organized as follows:

• Risk Model Development: A structured collision risk model is created using the Accident/Incident Model (AIM), identifying operational hazards, accident precursors, and safety barriers. This model serves as the foundation for quantifying risk under different operational conditions.
• Definition of Operational Environments (OEs): The airspace is classified into standardized Operational Environments based on factors such as airspace class, population density, UAS traffic complexity, and availability of CNS infrastructure. Each OE is assigned a Target Level of Safety (TLS) and a minimum required Risk Ratio.
• Derivation of SPIRs: From the risk model and OE classification, the project defines Safety, Performance, and Interoperability Requirements (SPIRs) for surveillance and communication systems, ensuring proportionality between operational risk and technical capability.
• Implementation of 5G-based Surveillance: A multilateration (MLAT) system is developed using 5G Positioning Reference Signals (PRS) and Time Difference of Arrival (TDOA) techniques. This is supported by a high-performance SDR platform for signal reception and processing.
• Simulation and Software-in-the-Loop Testing: Realistic drone operations are simulated using PX4 autopilot and Gazebo in a SITL (Software-in-the-Loop) environment. The simulator accounts for factors like GNSS interference, wind, or signal degradation, and integrates the 5G MLAT system.
• Multi-USSP Conflict Detection:A multi-USSP simulation platform is developed, incorporating strategic and tactical conflict detection services. Strategic conflict resolution is based on spatial discretization using octree algorithms, while tactical conflict detection is enabled through real-time data exchange services.
• Validation through Flight Testing: Real-world flight campaigns are conducted to validate the surveillance system and compare results against simulation outputs, closing the loop between theoretical modelling, implementation, and operational verification.

Impacts

SPIRIT-UCS is expected to:

• Advance Europe’s leadership in performance-based drone traffic management through validated risk models and safety requirements for U-space.
• Enhance the safety and scalability of low-level airspace operations by aligning surveillance and communication systems with operational risk.
• Promote the adoption of 5G-based surveillance technologies for accurate and cost-efficient UAS positioning in complex environments.
• Enable harmonized U-space services through interoperable multi-USSP conflict detection and coordination tools.
• Support regulatory development by providing quantifiable SPIRs tailored to different operational environments and risk levels.
• Strengthen collaboration between academia, authorities, and industry through contributions to EUROCAE, RTCA, and SESAR-aligned initiatives.