Astroshield AI
Astroshield AI is a high-performance Digital Twin platform for Space Traffic Management (STM). It processes real-time TLE telemetry for the active Low Earth Orbit (LEO) population, utilizing advanced spatial algorithms to predict kinetic collision risks and safeguard critical space infrastructure.
Key Features
- Spatial Physics Engine: Replaced brute-force proximity checks with a KD-Tree spatial indexing algorithm (via SciPy). This allows for sub-second conjunction analysis across 15,000+ orbital nodes by utilizing multi-dimensional binary search trees.
- Live TLE Ingestion Pipeline: Engineered a dynamic data pipeline that merges live Celestrak API traffic with debris cloud datasets (e.g., Iridium-33 fragments). Implemented data-source labeling to ensure ephemeris integrity and mission-ready verification.
- High-Fidelity 3D Situational Awareness: Developed a hardware-accelerated 3D environment that automatically categorizes and renders orbital objects. Implemented tactical color-filtering (Red-Threat-ID) to differentiate lethal debris from active assets in real time.
- Engineering-Grade Evasion Analytics: Built an autonomous maneuver module that calculates specific mission metrics, including Required Delta-V, Burn Duration (seconds), and Propellant Mass Cost (kg), achieving a theoretical maneuver success rate of ≥92%.
- Environment-Agnostic Architecture: Architected a resilient backend using dynamic Base Directory logic and /tmp/ buffer handling, ensuring seamless stability across Local, Cloud, and high-latency environments.
- SGP4 Physics Integration: Leveraged Skyfield for rigorous SGP4 orbital propagation, accounting for atmospheric drag and geopotential perturbations to generate precise UTC state vectors.
