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A CAA Sandbox project trialing "Shared Airspace Zones" where crewed and uncrewed aircraft operate simultaneously using ground-based Detect and Avoid.

LIMA (Local Integrated Management of Airspace) was a consortium project designed to prove that commercial drones could operate safely in shared airspace without TDA segregation. It utilized the 4DSKY network to provide situational awareness to both drone pilots and general aviation, effectively creating a "TCAS-like" separation service using ground infrastructure rather than expensive onboard avionics.
University of Southampton (Lead), Neuron Innovations, Windracers, Distributed Avionics, CAA Sandbox.
Achieved "High-Priority" status within the CAA Sandbox. Successfully completed Phase 1 test flights at Llanbedr, demonstrating safe separation protocols and informing the technical proposal for permanent shared airspace structures in the UK.1
General Aviation: Ensures safety without requiring expensive equipment upgrades.Logistics Operators: Allows flights in airspace that cannot be closed (e.g., near busy transport hubs).Regulators: Provides data on "mixed-mode" traffic interactions.
The Economic Barrier of Avionics Project LIMA addressed a critical economic constraint in the aviation industry: the cost and weight of onboard avionics. In the traditional aviation world, collision avoidance relies on Transponder Collision Avoidance Systems (TCAS). However, small delivery drones and many light General Aviation aircraft cannot carry the heavy, power-hungry, and expensive hardware required for TCAS. This creates a safety gap.
Ground-Based Detect and Avoid (GBDAA) LIMA validated a revolutionary concept: Ground-Based Detect and Avoid (GBDAA). In this architecture, the "intelligence" of the collision avoidance system is moved from the aircraft to the ground network. The 4DSKY sensor mesh acts as the "eyes," tracking all cooperative traffic in the zone. The ADEX software calculates conflict trajectories on the ground and uplinks avoidance maneuvers to the drone via the Command and Control (C2) link. This approach shifts the cost burden from the aircraft operator to the infrastructure provider, lowering the barrier to entry for drone logistics.
Algorithmic Innovation in Uncertainty Management One of the key technical challenges addressed in LIMA was managing the uncertainty inherent in sensor data. Multilateration (MLAT) precision degrades with distance and poor geometry. The project involved the development of advanced conflict resolution algorithms that incorporate "uncertainty volumes" around each aircraft. Rather than treating an aircraft as a single point, the system treats it as a probability cloud. If the probability clouds of two aircraft intersect, an avoidance maneuver is triggered. By proving that a decentralized ground network could provide "TCAS-equivalent" safety levels using these probabilistic models, LIMA opened the door for low-cost airspace modernization.
Regulatory Impact: The "Shared Zone" LIMA's acceptance into the CAA Sandbox and its subsequent "High Priority" status signaled a major shift in regulatory thinking—moving away from "segregation by default" toward "integration by capability." The data gathered from LIMA fed directly into the CAA’s evolving policy on Radio Mandated Zones (RMZ) and Transponder Mandated Zones (TMZ). Specifically, it validated the concept that a drone does not need to see an aircraft to avoid it; it just needs reliable data about where the aircraft is. 4DSKY provides that data.
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