Perspectives

3 Accelerators for Space Domain Awareness

Transform space traffic management and defense missions

The race is on to develop space capabilities for a growing array of national security, civil, and commercial priorities. With the satellite population expected to reach as many as 100,000 assets by the end of the decade, the challenge of keeping track of all those orbital objects and associated debris is formidable. Add analysis for critical missions, and it’s clear that space domain awareness needs to transform faster.

While details on 18th Space Defense Squadron operations and the transition of civil space traffic management (STM) to the National Oceanic and Atmospheric Administration (NOAA) Office of Space Commerce (OSC) are being finalized, stakeholders can focus on evolving technical capabilities by doubling down on data.

Here are three areas where forward-looking space organizations can move ahead—using technologies that are available today.

1. Integrate data across channels, partners, and classification levels

Fusing data from satellites across orbits onto one platform is essential for the emerging space ecosystem. Pulling in sensor data from partners around the globe—such as radar, optical, microwave radiometer, and infrared—and integrating it with data such as self-reported ephemerides will enable a new level of precision.

Think of the information national security experts will reap by adding unclassified data from commercial space service providers, civil agencies such as NASA and NOAA, and diverse signals intelligence—all curated and moved into a classified multi-intelligence framework. Likewise, civil agencies like OSC as well as commercial companies will gain more detailed data on environmental changes in remote areas, for example, by gaining access to declassified intelligence data. And all space organizations will capture the benefits of planning their missions with greater confidence.

2. Process that information for more accurate algorithms to fuel better predictions

Yesterday’s models won’t work for tomorrow’s missions. Take collision avoidance, for example—a key use case for space traffic management. In the past, when there were fewer space assets and more predictable maneuvers, simple drag models, propagation algorithms, and gravitational models sufficed for space traffic managers to assure collision avoidance. Now, with an estimated 670,000 objects larger than 1 cm floating in space, and thousands of programmable objects moving in and out of orbit¹, operators need to know precisely where their assets are relative to everything else.

Aggregating and fusing the data will enable new artificial intelligence (AI)/machine learning (ML) algorithms, accelerated with powerful graphical processing units for increasingly sophisticated, highly accurate modeling and simulation. For example, factoring in data on solar effects and the calculations of space object motion by powerful astrodynamics engines will help data scientists build accurate drag models for space objects traveling through the upper ionosphere.

These drag models will, in turn, inform sophisticated propagation models developed for varied use cases. Analysts and operators will receive more accurate data faster—operators only partially comply with maneuvers from a conjunction event (e.g., only 50% of operators maneuver when given a conjunction warning²).

3. Optimize the models for projections and forecasts

Knowing where an object will be at a future date will give stakeholders the advantage of acting preemptively (for example, to correct or optimize a flight path). It also will enable trend analysis, for example, to determine intent when surveilling the behavior of a rival nation’s satellite.

This also enables automation, which will be critical for fast response. In the past, agencies needed to know of events that might occur next week—now, they need to know what can happen in the next moment. Therefore, space agencies will need not only automated alerts but also automated courses of action. And all must be delivered via user-friendly, intuitive interfaces.

Capabilities

Artificial Intelligence for Space Missions

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Capabilities

Realize strategic as well as tactical benefits

These AI-powered capabilities will go beyond modernizing space traffic management to delivering advantages across missions. A few examples:

National security analysts will have the capabilities for rapid battlespace characterization—for example, knowing whether an object approaching a satellite is a rival’s space asset with hostile intent or merely space junk. Critical for military command and control, they’ll be able to deliver intelligence to warfighters so they can act faster than the adversary.
Space exploration specialists will be able to create more accurate launch projections, in addition to leveraging rapid analysis to optimize paths for space traffic going to and from the moon—a new category of orbit.
Environmental analysts will be able to analyze space weather patterns and effects so they can model and forecast changes in everything from precipitation and runoff to potentially catastrophic events, giving earlier warnings to space operators and protecting national assets.

Speed transformation with true open architectures

Today Booz Allen is putting the technologies to accelerate all these advances into practice, transforming space missions that range from national security to space exploration. We apply decades of mission knowledge to innovation featuring open architectures, flexible data frameworks, integrated data “fabrics,” and rigorous DevSecOps. Here are some highlights:

Using commercial software that integrates seamlessly across platforms, we connect open, cloud-native data platforms. This allows plug-and-play integration from any vendor. For example, for one client we were able to source and sample best-in-breed, commercially available propagation algorithms resulting in rapid modernization at less cost.
Helping the Air Force design and develop Platform One, the federal government’s first DevSecOps enterprise-level service, allows us to leverage ready-made capabilities—delivering the power of big data with the flexibility of microservices and small components for rapid, secure upgrades.
Our partnerships with leaders like Amazon Web Services, Microsoft, and Google allow us to bring clients seamless access to the newest technologies. And working with both commercial and government data gives us experience rapidly integrating data across disparate platforms—for example, calibrating sensors displaying different signature characteristics.
Our data-centric communications infrastructure enables data sharing with “bring your own network” flexibility, secured with a zero-trust framework providing granular protection at the data level.
Intelligence clients are using our solution that moves commercial and other unclassified data into classified environments, as well as our cross-domain solutions framework allowing classified data to move to unclassified.

The open architectures that enable these flexible advances will not only further space domain awareness but also empower initiatives from developing tomorrow’s intelligence space systems to equipping satellites for AI processing at the edge. It’s all possible by using the power of data—across modular, interoperable frameworks that put the mission in control.

References

1. Garcia, M. (2021, May 27). Space Debris and Human Spacecraft. NASA.gov. Retrieved November 30, 2022, from https://www.nasa.gov/mission_pages/station/news/orbital_debris.html

2. Borowitz, Mariel, Brian C Gunter, Megan Birch, and Richard J Macke. “An Investigation into Potential Collision Maneuver Guidelines for Future Space Traffic Management,” 2021. https://amostech.com/TechnicalPapers/2021/Conjunction-RPO/Borowitz.pdf.