GlobVision Inc.

Published purpose

The proposed project is to design, develop and integrate advanced machine learning and data analytics methodologies to automatically examine time series of Two-Line Elements (TLE) of space objects in SSN (Space Surveillance Network) catalog and detect novel/anomalous trends. A two-line element set (TLE) is a data format encoding a list of orbital elements of an Earth-orbiting object for a given point in time. Furthermore, the advanced methodologies will identify the root cause of the detected anomalies as either invalid TLE (due to erroneous satellite tracking data) or out-of-character space object behaviour. The proposed “TLE Trend Analytics” solution will redefine satellite monitoring and space intelligence through its automation and artificial intelligence capabilities, and will result in increased space situational awareness and increased reliability for the Canadian national defence.