SPACE ENVIRONMENT MODELS
Unlock unprecedented space environment intelligence with our advanced ionospheric modeling solutions and data services. From real-time atmospheric monitoring to predictive decision support, we transform complex environmental data into strategic operational advantages, providing unparalleled space domain awareness.
DRAGSTER
As space becomes a more hostile and contested environment and as commercial activities in low earth orbit (LEO) rapidly expand, the need for high-fidelity tracking is growing fast. The U.S. Space Force now tracks more than 29,000 objects in LEO—up from 20,000 just a few years ago. To meet this challenge, Orion developed Dragster, a cutting-edge solution that overcomes the limitations of existing atmospheric drag models. Its advanced assimilative framework optimizes performance by leveraging a custom-curated ensemble of models for each task. As these models evolve, future improvements will flow directly into Dragster performance, ensuring continuous advancement in space object tracking.
M3SDA
Orion is transforming ionospheric modeling and forecasting with a groundbreaking approach that reimagines how modern datasets, advanced computing and atmospheric assimilation techniques can be leveraged for the ionosphere. Our Modular, Modern, Model for Space Domain Awareness (M3SDA) tool is a modular framework that efficiently assimilates diverse datasets for forecasting space weather and its impacts.
OrbitIQ
Orion’s OrbitIQ delivers high-fidelity orbit modeling and forecasting to support accurate orbit determination, conjunction assessment, and the detection of maneuvers or deceptive actions in space. Hosted by AWS and driven by a dynamic digital twin of the space environment, OrbitIQ models complex interactions between the thermosphere, ionosphere, and satellites to provide real-time awareness and predictive insights. Offered as a Data-as-a-Service (DaaS) platform, OrbitIQ gives satellite operators and SDA analysts on-demand access to the information they need to navigate an increasingly contested domain with confidence.