AI-Driven Space Situational Awareness
Monitor, classify, and track satellites and space debris in real-time using neuromorphic vision and AI-powered analytics — built for defense, research, and resilient space operations.
EtherX AI’s SSA system leverages neuromorphic sensors to detect and analyze minute changes in space object motion and brightness. Unlike traditional frame-based cameras, our event-driven architecture captures only meaningful activity — enabling high-speed, low-latency tracking of satellites, debris, and unknown objects with unmatched precision.
Track fast-moving satellites and debris in low Earth orbit using ultra-low-latency, event-based sensing.
Detect unstable rotations with high temporal accuracy — using brightness variation and motion patterns.
AI-powered clustering separates stars, satellites, and unknowns, even in cluttered fields of view.
Cluster centroid tracking and motion prediction enables automated trajectory estimation and collision alerting.
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Unlike traditional cameras, event-based sensors capture only changes in the scene, resulting in ultra-low latency and reduced data noise—perfect for high-speed satellite tracking.
Our custom-trained machine learning models analyze motion vectors and brightness changes to accurately classify stars, satellites, and debris in real time.
With built-in processing capabilities, our edge devices run AI inference on-board, eliminating transmission delays and enabling responsive autonomous tracking.
Event data is processed using clustering algorithms that group related pixel activity by velocity (vx, vy) and centroid position, enabling reliable object detection.
Real-time motion trajectory prediction helps forecast orbital paths and determine collision threats before they materialize.
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