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C-CORE has also been awarded two contracts by the Canadian Space Agency (CSA) under the agency’s Earth Observation Service Continuity initiative from its Space Technology Development Program (STDP).
The first contract, which is worth up to $238,000, is for a new satellite instrument to better measure sea ice thickness for weather predictions and climate change monitoring. The second contract (“Intelligent Early Anomaly Detection and Failure Prediction Support Tools”) for up to $750,000 is meant to detect spacecraft anomalies early by analyzing satellite telemetry. (An identical contract has been awarded to Calian Advanced Technologies.)
All told, the CSA has awarded $6.8 million under ten contract categories to develop improvements for the next generation of Canadian Earth Observation (EO) satellites. They will be launched after the currently in-service RADARSAT Constellation Mission (three EO satellites) is retired.
The ‘ice thickness measurement from space’ contract will build on a previous design developed by C-CORE for a similar airborne ice thickness measurement capability, said Chris Fowler, Director of C-CORE’s Systems Group.
“The project will evaluate potential technology options, develop modeling and simulation tools, define key operating requirements, and establish a path for future technology development,” he told SpaceQ. “The approach for this work relies on the use of a VHF-band radar. Radar pulses are emitted from the satellite and impinge on the ice sheet. Radar energy is reflected from the various interfaces within the ice sheet such as the air-snow interface, the snow-ice interface, and the ice-water interface. The reflections from these interfaces are resolved from the returned signal to determine the thickness of the ice.”
C-CORE hopes to generate benefits from this CSA contract that go well beyond this project. “If this technology reaches its full potential, it could be the basis for a new class of payload capable of directly measuring ice thickness from space,” Fowler said.
The Intelligent Early Anomaly Detection and Failure Prediction Support Tools contract will “detect, prevent and/or mitigate known and new anomalies in spacecraft telemetry data to better manage the lifecycle of EO satellites,” said Michael Henschel, C-CORE’s Director of GeoAnalytics, which develops next-generation EE technology at the company. “The result will be the introduction of a tool based on machine learning (ML) techniques to analyze near-real-time telemetry data for satellite and sensor health. Small changes in telemetry, the information communicated to the earth from a satellite, whether in EO data feeds or instrument/orbit reporting may provide information about the state of the satellite that would be missed in normal operation – without the use of machine learning techniques to study the telemetry feed.”
Tapping into ML to detect anomalies through the ‘behaviour’ of satellite telemetry is a logical method for achieving early detection, and the chance for ground-based engineers to deal with such issues before they become serious. At the same time, “this is an emerging field,” said Henschel. To make this ML-based method work, “the researchers and engineers at C-CORE will be developing new tools and working at the cutting edge of new technology development. This project will contribute to the body of work that is developing in remote test processes specifically for an orbital environment.”
