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AMAN1011011
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Feature Description
With the rapid increase in the number of resident space objects (RSOs), including satellites, accurate orbit tracking has become crucial to prevent collisions and manage space traffic effectively. This project focuses on predicting the positions and speeds of 600 satellites, leveraging advancements in satellite technology, data analytics, and predictive modeling. By analyzing historical orbital data and utilizing machine learning algorithms, we aim to provide reliable and accurate long-term forecasts of satellite trajectories. These predictions will help in enhancing collision avoidance strategies, optimizing satellite operations, and mitigating the risks of space debris. Ensuring precise orbit tracking not only safeguards active satellites but also contributes to the sustainability of space activities.
Use Case
Collision Avoidance Satellite Fleet Management Space Traffic Management Mission Planning Space Debris Monitoring
Benefits
Enhanced Safety Operational Efficiency Cost Savings Improved Space Traffic Coordination Support for Long-Term Space Sustainability
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No response
Priority
High
Record