Space Object Tracking Data
Slingshot's Global Sensor Network offers comprehensive space object tracking data from LEO-to-xGEO, day and night, ensuring mission coverage with ground-based electro-optical tracking. This persistent and accurate data serves satellite operators, defense agencies, and space agencies with routine and event-based insights. With 20+ global sensor locations, 150+ day/night optical sensors, and over 500 million observations collected, Slingshot provides high-revisit rate tracking for active space events like maneuvers, conjunctions, and launches.
Astrometric Data and Spacecraft & Launch Database
Slingshot's astrometric data powers state and covariance estimates, maneuver detections, and behavioral insights. Additionally, Slingshot Seradata offers detailed data on every launch attempt and spacecraft deployed into orbit. It serves as the leading satellite and launch database in the industry, providing customers with up-to-date views on launch and satellite industry activities, trends, failure rates, and more.
Conjunction Assessment Data and GNSS Data Integration
The platform enables users to screen for conjunctions using a commercial space object catalog, offering high-accuracy results. Users can upload their own ephemerides to facilitate risk assessment. Moreover, users can input GNSS telemetry to generate orbit determination states and predicted ephemerides, enhancing mission planning and risk evaluation. The platform also supports custom screening services for conjunction scheduling.
Pattern of Life Insights and Neighborhood Watch Insights
Pattern of Life Insights combine satellite descriptors, orbital characteristics, and maneuver detection to provide detailed insights into spacecraft behavior. Alerts notify users of changes in spacecraft behavior. Neighborhood Watch Insights offer real-time information about satellite clusters in the GEO belt, monitoring neighbor characteristics and behaviors. Reports enhance space domain awareness by detailing neighborhood shifts and maneuver patterns.
AI Outlier Spacecraft Insights and Radio Frequency Signal Insights
Slingshot's Agatha AI monitors and identifies outlier satellites within constellations by detecting anomalous behavior. The AI algorithms provide built-in explainability and scalable architecture for efficient outlier identification. Additionally, Radio Frequency Signal Insights offer analysis of RF signals, enabling users to gain valuable insights into spacecraft communications and operations.