LEO-xGEO SPACE DOMAIN AWARENESS
Space Domain Awareness
Leverage Slingshot's solutions for persistent space domain awareness that supports the most demanding missions from LEO to GEO & beyond.
Leverage Slingshot's solutions for persistent space domain awareness that supports the most demanding missions from LEO to GEO & beyond.
Slingshot's space domain awareness solutions provide observational and analytical insights through persistent space object tracking, advanced space data fusion, and machine learning-driven object behavior insights. Whether you need to track specific spacecraft over the long-term or monitor active space events in real-time – Slingshot has eyes on.
Unlock astrometric and photometric insights from the Slingshot Global Sensor Network – day & night from LEO to xGEO.
Employ Slingshot’s proprietary software for advanced uncorrelated track processing, orbit determination, and maneuver detection.
ML-driven object behavior insights provide near real-time insights into satellite behavior.
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The Slingshot Global Sensor Network provides around-the-clock tracking of spacecraft and debris from the world’s only optical day/night LEO-to-xGEO spacecraft and debris tracking network.
Our high-quality astrometric data fuels many derived data products such as state and covariance estimates, ephemerides, CDMs, maneuver detections, and other types of physical and behavioral characterization insights. Photometric data can be used to detect and identify anomalous behaviors and characterize space objects.
Maintain custody of active spacecraft and space debris across regimes to ensure up-to-date cataloging and improved space domain awareness regardless of where an object of interest maneuvers.
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Slingshot’s Multiple Frame Assignment Space Tracker (MFAST) software provides advanced, scalable uncorrelated track (UCT) processing, orbit determination (OD), and maneuver detection (MD) by fusing data from multiple sensors and/or sensing modalities.
Fuse data from radar, passive radio frequency (RF), ground-based-optical, and space-based-optical sensors to track objects from LEO to xGEO.
Slingshot MFAST is used operationally by government customers around the world to quickly resolve uncorrelated tracks (UCTs) that result from large maneuvers, breakup events, and new launches.
Customized astrodynamics and multi-hypothesis-tracking algorithms provide scalability and highly-accurate, near real-time orbits for government and commercial use cases.
MFAST has been actively used by the United States Government since 2019 to enable uncorrelated track resolution, which has led to the recovery, update, and identification of thousands of objects, and the successful processing of over 10 breakup events.
ML-driven object behavior insights provide near real-time insights into satellite behavior.
Slingshot’s pattern of life insights use satellite characteristics, orbital analytics, and maneuver detection and classification to generate detailed and actionable insights.
The neighborhood watch insights analytic provides near real-time information about clusters of satellites in the GEO belt. The algorithm evaluates the general characteristics of grouped satellites (“neighborhoods”) and monitors for changes in those groups.
Identify anomalous spacecraft behavior and uncover hidden insights with a scalable machine learning algorithm that detects subtle differences between object behavior across large space datasets with built-in explainability.
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Slingshot’s optical observation data and space data fusion capabilities are leveraged by government agencies around the world to enhance their space domain awareness.
The Slingshot Global Sensor Network delivers millions of observations per year to the Joint Commercial Operations cell to support their continuous monitoring of the space domain.
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