The Slingshot Platform provides mission-critical data and insights to satellite operators, defense agencies, and space agencies around the world.
LEO-to-xGEO, day and night, Slingshot's Global Sensor Network has your mission covered with persistent, ground-based, electro-optical space object tracking.
Slingshot's comprehensive, accurate, and actionable tracking data serves a range of satellite operators, defense agencies, and space agencies who require both routine and event-based insights.
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.
Light curve data, derived from our ground-based imagery, aids in object characterization, including pose and rotation rate estimation, along with other physical properties.
Sub-arcsecond astrometric accuracy and frequent calibrations against public sources provide data you can trust. Single-digit minute latency ensures data is delivered on operationally-relevant timelines.
Consistent tracking of objects of interest with data provided daily to help ensure safe operation of your spacecraft.
High-revisit rate tracking through customizable, mission-specific tasking that can be adjusted to meet customers' unique mission needs.
High-revisit rate tracking and dedicated orbital analyst support for active space events such as maneuvers, conjunctions, and launches.
Slingshot Seradata provides detailed data on every launch attempt and spacecraft deployed into orbit. As the industry’s leading satellite and launch database, it is updated daily with new satellite and launch data – providing a comprehensive, up-to-date view of the entire space industry.
Customers across the industry leverage Slingshot Seradata to analyze launch and satellite industry activity, trends, failure rates, market share, insurance claims, and more.
Leverage our comprehensive and high-accuracy commercial space object catalog to regularly screen for conjunctions at whatever cadence meets your unique operational needs. Upload your own operational or special ephemerides to screen against our catalog to facilitate mission planning and risk assessment.
Take control of your conjunction screening schedule by leveraging our high-accuracy custom screening services. Just launched? No problem! Our ephemeris screening service in Slingshot Beacon can generate CDMs based on both your catalogued and uncatalogued objects.
Enhance your understanding of any given conjunction by leveraging our space object tracking service. Resulting data products, such as raw observations, OD states, predicted ephemerides, and CDMs, can be made available via our Slingshot Platform APIs.
Provide your GNSS telemetry to our Orbit Determination-as-a-Service system to generate orbit determination states and predicted ephemerides. Ephemerides can then be used in Slingshot Beacon, or input to our conjunction screening service, to screen for conjunctions and evaluate the associated risk.
Slingshot's Pattern of Life Insights analytic combines satellite descriptors, orbital characteristics, and maneuver detection to offer detailed and actionable insights into a spacecraft's behavior.
Users can receive near real-time alerts about objects of interest when a spacecraft’s behavior has changed or deviated from what is expected – or view reports on historical actions and potential future actions.
Understand how any satellite has been maneuvering with maneuver history, drift history, longitude history, station keeping changes, and flagged behavior change – and be the first to know when there is a change.
Understand the mission phase of every satellite and be the first to know when its mission phase changes. Phase Change reveals long-term patterns and events of interest, including: Pattern of life characterization, changes of object status from active to inactive... or vice versa, and shifts to disposal orbits.
Keep tabs on the satellites operating near your spacecraft. Receive reports on their mission phase and behavior over time, allowing for fast and accurate response and risk mitigation when issues arise.
Discover satellites that exhibit similar behavior patterns, based on global information and fine-grained maneuver and orbital analysis. Find unexpected similarities in pairs of objects, help to anticipate potential actions of unknown satellites based on similar known satellites, and improve awareness on general maneuver patterns of groups of objects.
Pattern of life insights can be quickly and easily pulled into reports detailing the behaviors exhibited by a satellite over its lifespan. Operators can easily access all available information in a single package for better space situational awareness.
The Neighborhood Watch Insights analytic provides near real-time information about clusters of satellites in the GEO belt by evaluating the general characteristics of grouped satellites (“neighborhoods”) and monitoring for changes in those groups.
Slingshot flags observations in near real-time when new neighbors arrive, when the inter-satellite distances change, when behaviors of the existing neighbors change, or when individual satellites leave.
Stay on top of satellite activity around your craft with drift detection, inspector satellite detection, and future target prediction for stalker satellites.
Be informed of the most interesting activity happening in space with our prioritized High-Interest Watchlist, which provides near real-time updates on new or interesting activity alongside detailed reports and analytics.
Receive alerts when satellites in your neighborhood exhibit new and unexpected behaviors, improving safety and providing transparency into activity around your spacecraft.
See how a satellite’s neighborhood changes over time by examining the history of satellites in the neighborhood, distances between satellites, past maneuvers, and past behaviors. Improve comprehension of alerts in the present day with easy comparison to similar historical events.
Receive automated reports detailing characteristics of neighborhoods around the GEO belt, along with common shifts in behavior and maneuver patterns, improving your GEO space domain awareness.
Whether trying to understand the impact and operation of orbital neighbors or maintaining awareness of suspected threats, Slingshot's Outlier Spacecraft Insights provide real-time monitoring of active constellations.
Machine learning algorithms identify anomalous spacecraft behavior and uncover hidden insights by detecting subtle differences between spacecraft behavior across large constellations, identifying unique behaviors for further investigation and helping operators make more informed decisions on orbit.
Slingshot’s algorithms identify anomalous satellite behavior through parallelized analytics including inverse reinforcement learning and unsupervised machine learning models.
Outlier Spacecraft Insights can efficiently search a vast space of tens of thousands of correlations against millions of data points. It has been tested against 600M+ real and simulated data points in 35+ scenarios.
Machine learning algorithms extract relevant features with respect to each individual constellation. This allows metrics to be calculated for each individual satellite in the context of its larger collective, facilitating the identification and characterization of disparate members and behaviors.
Slingshot's algorithms have built-in explainability that indicates why a specific satellite's behavior has been flagged as an outlier.
Slingshot’s Radio Frequency (RF) Signal Insights enable partners to identify, track, and characterize ground- and space-based RF sources including jammers, spoofers, and unexpected sources.
Slingshot utilizes Global Navigation Satellite Systems (GNSS) data to detect signal degradation, geolocate interference sources, and characterize the pattern of life of each RF source. This allows satellite operators to better understand and manage nefarious or unexpected RF sources that may jeopardize their missions.
Real-time data monitoring services are available to continuously analyze and monitor known and unknown RF signals to detect and characterize anomalies.
Perform retroactive RF interference investigations informed by empirical measurements where interference sources are identified, geolocated, categorized, and indexed for lifecycle characterization.
Slingshot utilizes cutting-edge computer-aided design (CAD) models, material attribution, and high-fidelity physics modeling to generate interactive 3D visualizations, giving partners the tools they need to comprehend and visualize the complex RF environment.