Sierra Space enhances orbital debris tracking with NVIDIA collaboration

Sierra Space enhances orbital debris tracking with NVIDIA collaboration
by Clarence Oxford
Los Angeles CA (SPX) Dec 11, 2024

Sierra Space, a prominent commercial space company dedicated to Building a Platform in Space to Benefit Life on Earth, has unveiled an important advancement in space domain awareness. In collaboration with NVIDIA, the company is employing physics-informed neural networks (PINNs) to more accurately forecast the trajectories of orbital debris.

As the accumulation of orbital debris intensifies, precise and dependable prediction models are increasingly vital for safeguarding space assets. Traditional models often struggle with the complexity of orbital dynamics. Sierra Space's approach integrates physical principles directly into neural network frameworks, significantly boosting prediction accuracy while reducing computational demands.

"At Sierra Space, we are committed to pioneering innovative solutions that ensure the safety and operational integrity of our space assets. By leveraging physics-informed neural networks and collaborating with NVIDIA, we are setting a new standard in space domain awareness," said Sierra Space CEO Tom Vice. "This advancement not only enhances our ability to predict the future locations of orbital objects with unprecedented accuracy but also significantly improves the computational efficiency of our models. Together, we are making space safer for all."

Harnessing Physics-Informed Neural Networks for Accurate Predictions

PINNs introduce a sophisticated methodology for predicting orbital debris behavior. By embedding fundamental physical laws into neural networks, these models can simulate the intricate forces influencing debris movement. The result is a system capable of delivering more precise forecasts of orbital debris paths and potential intersections with spacecraft.

Sierra Space's PINNs integrate diverse datasets, including satellite observations and historical tracking data, to generate real-time predictions. This combination of data-driven insights and physical principles enables operators to take timely and effective measures to avoid collisions, ensuring operational safety.

NVIDIA's Role in Advancing Computational Efficiency

Sierra Space's cutting-edge space domain awareness relies on its collaboration with NVIDIA. NVIDIA's AI and accelerated computing platforms enable efficient training and inference processes for PINN models, critical for managing the heavy computational requirements of deep learning applications.

NVIDIA GPUs, optimized for parallel data processing, dramatically reduce the time needed for model training and predictions. These capabilities are essential for real-time applications, where prompt and accurate forecasting can avert potential collisions.

"At Sierra Space, we are constantly pushing the boundaries of what is possible in space. By leveraging the power of NVIDIA accelerated computing and deep learning, we are not only enhancing the accuracy of our predictions but also ensuring the safety and operational integrity of our space assets," said Dr. Joe Kopacz, Sierra Space's Vice President of Software Engineering and AI Strategy.

"Our collaboration with NVIDIA has been instrumental in achieving the computational efficiency required for real-time applications. This advancement marks a significant milestone in our mission to protect the space environment and ensure sustainable operations for the future."