Today’s space operations environment is more complicated than ever. The number of man-made objects in space is rapidly increasing, while the range of space activities is evolving. Additionally, the number and variety of sensors monitoring space object behavior continues to increase. These factors lead to an increasingly-complicated analytics challenge in resolving uncertainty, developing a trusted base of knowledge for space objects, and driving efficient data collection.

ExoAnalytic autonomously collects, processes, correlates, organizes, and maintains feature data and meta-data for all observed man-made space objects in SpaceFront, our data warehousing and analytics engine. SpaceFront serves as a unique and robust data repository for more than 100 million observations collected by our global telescope network. This enables rapid analysis of man-made space object behavior with cutting-edge algorithms, dynamic charting, and a multitude of analysis tools.


SpaceFront provides instant access to all current and historic metric, non-metric, and meta data collected for all space objects observed by the ExoAnalytic global telescope network. Photometric (brightness) data is maintained for all observed space objects. Brightness data from a single night can be used to infer object size and stability. The aggregation of brightness data enables the development of unique signatures, or fingerprints, that we utilize to correctly identify and characterize satellites and their behavior.


ExoAnalytic has developed a suite of analysis tools that enable the rapid, and in some cases real-time, detection of anomalous behavior of space objects. We utilize our unique fingerprints for all man-made objects in SpaceFront to develop automated change detection and identification tools that can alert our team to unusual activities in space. These capabilities serve as an invaluable tool supporting operational anomaly resolution and forensics.


Within SpaceFront we identify, store, and catalog the long-term behavior of man-made space objects in an attempt to understand each object’s pattern of life. The frequency of maneuver, maintenance of orbital position, seasonal attitude adjustments and other standard behaviors are observes and cataloged. This enables analysts to predict expected behaviors of space objects, as well as rapidly identify deviations from expected behavior.

ExoAnalytic has extensive experience in the design, development, testing, and fielding of advanced algorithms for solving today’s complex space and intelligence challenges. Today’s sophisticated algorithms require a large amount of cataloged data that must be processed, filtered, and analyzed. Our database of more than 100 million measurements provides the feedstock for algorithm development and testing that enables us to provide unparalleled products.

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