Calian Awarded CSA Satellite Anomaly Detection Contract

The Canadian Space Agency (CSA) has awarded Calian Advanced Technologies (Calian) a contract worth up to $750,000 for analyzing satellite telemetry for the early detection of anomalies and/or possible failures. Officially known as the Intelligent Early Anomaly Detection and Failure Prediction Support Tools contract, part of the Space Technology Development Program, it is one of ten announced by the CSA on March 2, 2023. (An identical contract was also awarded to C-CORE for the same amount.) The ten contracts, which have been issued under the CSA’s Earth Observation (EO) Service Continuity initiative, are collectively worth $6.8 million. The initiative is meant to shape Canada’s next generation of EO satellites. They will succeed the RADARSAT Constellation Mission (RCM) trio of EO satellites currently in service. Calian has been providing flight operations, ground segment products, and services to government and commercial clients for over 40 years. The Intelligent Early Anomaly Detection and Failure Prediction Support Tools contract is aimed at improving satellite operations efficiencies by utilizing computing technology advances such as artificial intelligence (AI) and machine learning (ML). “Leveraging intelligent computational processes like artificial intelligence and machine learning, Calian intends to unlock mission efficiencies that were previously not possible with traditional systems,” said Dan Baril, Calian‘s Senior Vice President of Space. “The idea is to get the machine entity to monitor the same telemetry streams as the experts and learn from the experts how to identify and manage anomalies itself.” Using its in-house AI/ML experts, Calian intends to begin this project with an analysis of various AI methods and ML models to determine the best-suited performers for this project. “Collaboration with the company’s satellite mission domain experts will ensure the delivery of a further developed technology and culminate with a demonstration to the Canadian Space Agency,” Baril told SpaceQ. There are numerous platforms available to build a model, he added. “These need to be investigated and tested to determine which methods provide the best results for our use cases. Machine learning models can be tailored but some are better than others in certain cases. This project will identify which methods work best to identify satellite anomalies and predict on-orbit failures.” The Big Picture goal of the Intelligent Early Anomaly Detection and Failure Prediction Support Tools contract is to help Canada develop a new generation of EO satellites with cutting-edge, even unprecedented capabilities. That‘s a role that Calian feels its filling, through its work on this project. “Further development of this technology can be incorporated into existing mission operations as well the design of future missions,” said Baril. “(Establishing) A standard around which these future missions are developed is important as it helps reduce the time from concept to launch, reduces the amount of mission-specific training required for personnel and improves the overall efficiency of the Canadian satellite ecosystem.” Dan Baril also sees real opportunities for the CSA and Calian to harness this technology for the Low Earth Orbit (LEO) satellite industry as a whole. “It is well known that this market is expanding rapidly, and this project will be an important player in bringing new missions on-line with reduced overhead,” he said. “Looking to the broader increase in deployment of LEO constellations, our expectation is that this development will have applicability to the management of these satellite fleets. Management of such large fleets of satellites will surely depend on platforms such as this to optimize the lifetime of their space-based resources. They will provide the operations team with the agility and efficiency to be able to digest and analyze the vast scale of data that these large fleets produce.”