Early warning fault detection for satellite operations based on telemetry
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Project and Master Subjects 2025-2026
- Super-agile operation of small satellites
- Early warning fault detection for satellite operations based on telemetry
- Semi-controlled re-entry for a satellite using attitude control
- System identification of environmental effects for a satellite during re-entry
- Mu-analysis for agile satellite attitude control maneuvers
- Enabling high-accuracy HYPSO image georeferencing by high-accuracy satellite pose estimation through postprocessing of satelitte sensor data
- High-accuracy attitude determination of Earth observation satellites
- Starlink: Signals of Opportunity positioning, navigation and timing (PNT)
- GNSS-R: Simulator design of a GNSS-Reflectometry simulator
- GNSS-R: Payload and embedded SW design
- GNSS-R: GNSS jamming and spoofing source localization from space
- GNSS-R: Formation flying of small satellites
- GNSS-R: Novel ship-detection methods for GNSS-Reflectometry
- Automatic Satellite Telemetry Anomaly Detection and Trend Analysis
- Which works better, explainable AI or black-box AI?
- Integrating the HYPSO constellation with the Copernicus Suite
- Explainable AI on a GPU
- What can the HYPSO-3 Hyperperspectral Cameras Observe?
- Could a short-wave infrared hyperspectral imager characterize oil spills?
- Coordinated Planning between a satellite constellation and a Autonomous Surface Vehicle
- Calibration of Hyperspectral camera point-spread function
- Past Projects
Early warning fault detection for satellite operations based on telemetry (F25/S26)
Background
The NTNU SmallSat Lab launched our first satellite, HYPSO-1, in January 2022. The sibling satellite, HYPSO-2, was launched in August of 2024. Since then, the satellites have continuously downlinked data about system health – called telemetry data – and have been stored in a database. Telemetry has been used for understanding the health of the satellite and for troubleshooting when anomalies occur. However, long-term trends of HYPSO telemetry have not been studied. It is also desirable to look for indications of anomalies occurring, enabling preventative and controlled resolutions.
Impact
Uncovering long-term trends can help deepen our understanding of the satellite and possibly locate unknown issues allowing them to be addressed ahead of them becoming major issues. The industry is also interested in early detection of possible anomalies such that they can be addressed ahead of them leading to e.g., system halts, which in turn disrupt imaging schedules. The HYPSO-1 satellite has been orbiting the Earth in the harsh environment of space for more than 3 years already, which has led to some components not being functional anymore. Potentially uncovering unknown indicators of these malfunctions has the potential to improve the understanding and expectations for the more recently launched HYPSO-2 satellite.
Project Focus
The SmallSat Lab already has a tool that pulls all the telemetry data and sends an alert to the satellite operations team if a reboot has occurred. The aim of this project is to extend this by processing data to identify trends, anomalies, and possible indicators that an anomaly will happen. Focus areas cover general satellite health, but also analyzing its attitude estimates and control and power usage. In cooperation with the satellite operations team, discoveries will be discussed to suggest and implement changes in the satellite operations to address the findings.
Tasks and Expected Outcomes
The candidate will learn about anomaly detection and satellites, with in-depth knowledge of the HYPSO satellites. As the project progresses, the candidate will be able to implement changes to the satellite operations, allowing for analysis of their impact. The work will most likely be performed using python. The candidate will work closely with the HYPSO satellites, but the work is intended to be generalized for use in other satellite missions as well.
Who We Are Looking For
We are seeking a highly motivated final year student in Cybernetics, Electronics, or a related field with an interest in satellites, data processing, attitude control and programming. Previous satellite experience is not necessary. The project will be adapted to the student's background and goals.
How we work
At the NTNU SmallSat Lab we encourage collaboration and try to get our group to help each other. To facilitate this, we encourage the students to meet us in the lab as well as arrange common lunches and workshops where the students and supervisors can learn from each other.
For more information, please contact the following:
Jan Tommy Gravdahl, jan.tommy.gravdahl@ntnu.no
Simen Berg, simen.berg@ntnu.no
Bjørn Andreas Kristiansen, bjorn.a.kristiansen@ntnu.no