GlobVision has received a multi-year grant from Industrial Capacity Building Contribution program from the Canadian Space Agency to develop a TLE Trend Analytics solution that utilizes advanced artificial intelligence (AI), machine learning (ML) and big data analytics (BDA) methodologies to automatically examine time series of Two-Line Elements (TLE) of 20,000+ resident space objects in the SSN (Space Surveillance Network) catalog and detect novel or anomalous trends in their orbital behaviour. It will also 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.

Developing the intended TLE Trend Analytics solution will result in:

  • A tool that increases and enhances the know-how and capabilities of the satellite operations community who control and manage space assets within the government and the private sector.
  • New concepts that not only advance the current state-of-the-art but also transform and revolutionize Space Situational Awareness (SSA) and satellite monitoring.

The main innovations of the solution are:

  • Automatic detection of anomalous behaviour of any space object orbiting the Earth by analyzing its TLE time series.
  • Hybrid algorithms for novelty detection through fusion of model-based and data-driven (AI, ML, BDA) methods for time series analysis.
  • Distinguishing whether a detected anomaly is due to invalid TLE due to erroneous tracking data or a real out-of-spec behaviour; using semi-supervised and active learning methodologies.

Our advanced TLE trend analytics solution will be a highly innovative product with novel and unique capabilities that do not currently exist on the market. In addition to tremendous operational (and economic) values, it will re-define satellite monitoring and space intelligence through its automation and AI capabilities and will result in enhanced SSA with increased know-how, efficiency and reliability for Canadian national defence.