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Improving Space Domain Awareness with Prime Focus

Aerospace is advancing Space Domain Awareness capabilities with Prime Focus – a prototype automated SDA node.

As more nations and commercial entities have advanced space capabilities, strengthening Space Domain Awareness (SDA) becomes increasingly critical for the nation’s space operators to be cognizant of what else is operating in Earth’s orbit and beyond. Integrating and streamlining information across the enterprise is crucial in advancing that effort. Currently, data does not flow smoothly from photons to decision support tools for the warfighter, delaying real-time decision support.

The Aerospace Corporation is leading the way in establishing an operational pipeline for SDA sensors with project Prime Focus – a prototype automated SDA node.

A sample of tracking imagery on COSMOS2499.
A sample of tracking imagery on COSMOS2499.

“The current systems rely on human operators, making the pipeline fragile and prone to error,” said project lead Matthew Britton, Principal Engineer in Aerospace’s Space Science Applications Laboratory. “Prime Focus will yield a sustained, daily operational SDA data flow backed by digital engineering and cloud technologies.”

Space control and SDA is a technically challenging problem with many requirements: extensive sensor networks for observational capacity, geometric diversity for solar lighting conditions, broad ground sensor coverage, and response times on a tactical scale.

One foundational issue is how to use multiple heterogeneous sensors to collect data on a list of resident space objects that is growing at an exponential rate. This requires scheduling sensors, communicating observational tasks to them in real time, acquiring these observations autonomously, and reporting the data back to a central data store. Scheduling is a particularly complex problem with many variables, since the sensors, targets, Earth, and sun are all in relative motion. Artificial intelligence and machine learning are promising solution paths that can be leveraged to meet the timescales needed.

“An automated, self-scheduling network of sensors cries out for a solution that can accommodate the dynamic requirements imposed by both weather and tactical imperatives,” Britton said.

Prime Focus Tracking GEO Sat.gif
Videos tracking satellite against starfield.

Prime Focus is an effort to automate the 1-m AeroTel telescope located on top of Aerospace’s laboratory facility in El Segundo, Calif. AeroTel is well-suited to this project, with a range of existing instrumentation developed specifically for the SDA mission. User inputs will generate an automated observation schedule that respects solar lighting conditions.

AeroTel Instruments Telescope, 20201029-Past-1296.jpg
AeroTel, a 1-meter telescope, serves as the sensor testbed for project Prime Focus.

AeroTel will then perform these observations, write data products to cloud storage, and report outcomes to the users automatically. The node will rely on cloud infrastructure, cloud storage, and software management that is aligned with modern software practices. The Prime Focus concept can then be scaled to fill the SDA need to coordinate large numbers of sensors with multiple targets.

An initial demonstration of Prime Focus was successfully completed in September 2021, illustrating the methodology. Going forward into the near future, Prime Focus will serve as a testbed for scheduling, modeling and simulation, artificial intelligence/machine learning and image postprocessing, and will provide a sustained data flow out to external data centers. The goal is to demonstrate an autonomous SDA sensor node that can respond to scheduling events from other research institutions, industry, and government partners. In this way, the AeroTel telescope becomes a discoverable SDA resource to users both within and outside Aerospace in a modern cloud context.

Space catalog
The animation above provides a visual representation of just a small fraction of the orbital elements in the Space Catalog. SDA will require artificial intelligence/machine learning solutions as the space environment grows more contested and congested. Aerospace is pioneering new approaches to these challenging problems.

“Prime Focus demonstrates the digital methodology backing a geographically distributed ground sensor network, that scales to large node count,” Britton said. “This type of network addresses our customers’ hard problems in space control and space domain awareness that remain unaddressed by the current SDA architecture.”


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