This blog is part of a series exploring the technologies and principles shaping the future of simulation.
A training center has been running its simulator suite for eighteen months. Now operators are preparing for a mission in a new region. The intelligence office has fresh terrain and threat data, some of it too sensitive to leave the building.
Until the simulators are updated with that data, pilots and sensor operators cannot practice in the new environment. Can the training center make that update with its own people and its own data, or does it need to wait on someone else?
Sovereignty Means Control After Delivery
Before buying a training system, a program manager needs to know what the team can change on its own after delivery.
Operators can only prepare for what the simulator shows them, and what it shows comes from the data and assumptions loaded into it. As the last post in this series argued, whoever controls those inputs holds real authority over training readiness. When the terrain no longer matches the latest intelligence, the program needs to be able to fix it before operators rehearse on it.
That ability depends on choices made during acquisition. Can the system run at the customer’s site, where sensitive data needs to stay? Will the team have the tools and support to make updates? Aechelon’s simulation systems are designed around those needs, starting with the ability to keep the system and its data on site.
Aechelon Nucleus image generation system (left) and Nexus secure storage system (right), both installed and operated at the customer’s facility.
Keep Sensitive Data On Site
Classified intelligence comes with rules about where it can be stored and who can handle it. In our example, those rules mean the training center’s new terrain and threat data cannot leave the building. To use that data in training, the training center needs three things on site. It needs a system that generates the synthetic environment, storage for the classified data, and authorized people to support both.
The system is the image generator, the computer that draws what operators see out the window and on their sensor displays. Aechelon’s Nucleus image generator is installed at the point of need, on hardware the customer owns. It can run on a closed network with no connection to the internet or outside systems, so the classified data it uses never travels beyond the facility.
The data needs its own controls. New intelligence is often more restricted than the data already in the simulator, so a single site may hold data at several classification levels. Nexus, Aechelon’s secure data management system, keeps that data at the site and gives each simulator and user access only to what they are cleared to see.
Support also needs to be close by for integration and maintenance. Shield AI has offices across Europe, the Middle East, and Asia Pacific as well as the United States. With the system, the data and the support all in place locally, the training center can load the new intelligence under its own security rules and keep it there as the mission changes.
Examples of Shield AI’s broader work with local partners include announcements in Poland, Greece, and Spain.
The team starts with a map of the world and then adds its own data to it. Aechelon Global Database provides that starting map. Built on that sovereignty vision, SkyBeam™ will allow the team to add the new terrain and threat data to one area without rebuilding the rest, while keeping the visual and sensor views consistent with each other. The goal is for the training center’s own staff to make the change, check it, and prepare the environment for the next rehearsal.
Over a long service life, the program will also add equipment and content from other suppliers and allies. Two kinds of standards make that possible. Interoperability protocols, such as Distributed Interactive Simulation (DIS), High Level Architecture (HLA), and Common Image Generator Interface (CIGI) let the system connect with other simulation tools. Synthetic environment standards, such as Common Database (CDB), let the program add new content and reuse the databases it already owns.
Stay in Control When Training Together
Collaboration among nations gets complicated quickly without the right level of interoperability. Beyond linking simulators, each nation has to decide what it will share while keeping authority over the rest.
In a federated exercise, each nation’s simulators stay on its own systems and connect to a shared exercise. Each nation approves what the others can see. Shared standards make the connection, and the participants set the rules. Writing for the NATO Command and Control Centre of Excellence, Major General Dominique Luzeaux describes the goal as an arrangement where “participants can retain data sovereignty while maintaining coherent discovery and shared meaning.” Put simply, each nation keeps control of its own data, and everyone in the exercise can still find and understand the information they share.
Pragmatic sovereignty does not mean isolationism. The training center in our example can buy from an allied supplier and train alongside partners while retaining authority over its own environment. Hardware stays on prem, with sensitive data managed under the training center’s own security rules. The training center decides what becomes part of a shared exercise and who can access it.
Defining the Team’s Control
Before purchase, the program manager should establish which environment updates the training center can make and validate independently, and which require supplier support. The system requirements should make that division explicit. Sovereignty on the virtual environment pipeline is one part of training readiness. The other is making sure every view of it agrees, so the terrain a pilot sees matches what the sensors detect. In the next post, we explore how digital ground truth makes that possible.
Figure 1: Example platforms from Aechelon programs, which support more than 1,200 operational training and simulation systems across the U.S., NATO, and allied nations.
