Characterization of High-resolution Spectral Imager
- Project and Master Subjects 2025-2026
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Past Projects
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Project and Master Subjects 2024-2025
- Improving Images for Climate Action
- Every Variable Everywhere All at Once
- Protecting Water Resources through Machine Learning and Hyperspectral Imaging in Remote Sensing CubeSats
- More Effective Earth Observation for Climate Action Through Learned Data Compression in CubeSats
- Mitigating Camera Artifacts in HYPSO Data for Improved Climate Monitoring
- Characterization of High-resolution Spectral Imager
- A Foundational Unmixing Model for the HYPSO satellites
- Hyper/Multispectral image fusion with HYPSO-2
- Game theory applied to energy optimal satellite attitude control
- Mu-analysis for agile satellite attitude control maneuvers
- Randomized optimization applied to super-agile satellite operations
- Modelling super-agile satellite operations for optimization
- 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
- Agile Earth Observation Satellite simulation studies
- Multi-angle image analysis and what we can learn about the atmosphere
- GNSS-R: Simulator design of a GNSS-Reflectometry small satellite
- GNSS-R: GNSS jamming and spoofing source localization from a small satellite
- GNSS-R: Maritime Surveillance using GNSS-Reflectometry
- Project and Master Subjects 2023-2024
- Project and master assignments 2022
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Project and Master Subjects 2024-2025
Characterization of High-resolution Spectral Imager
Project Focus
A new satellite, HYPSO-3, with a 5-m resolution resolution imager is being planned. It will be able to see algal blooms inside fjords and lakes more clearly. There is a prototype imager for the satellite already. This thesis involves characterizing that imager through various optical tests.
Impact
Space technology plays a crucial role in achieving various Sustainable Development Goals (SDGs) set by the UN. The NTNU SmallSat Lab's HYPSO satellites, the first of which was launched in 2022, utilize hyperspectral imagers to capture detailed information beyond the visible. This data allows us to detect and monitor water bodies like oceans, fjords, and lakes, including vital yet potentially harmful algae.
Tasks and Expected Outcomes
NTNU is developing a high-spatial resolution camera for its next satellite, HYPSO-3. This project will involve radiometric, spectral, geometric, and stray light calibrations of the new HYPSO-3 hyperspectral camera. Once launched, the HYPSO-3 satellite will be used for water quality monitoring of fjords and lakes in order to help Norway achieve the UN's sustainable development goals.
Skills that will be learned
- How to use optical test set ups
- What camera properties are important to spectral imaging
- How cameras interact with other components in an autonomous robot (in this case, a satellite)
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 image processing and remote sensing applications. Experience with signal processing techniques is not mandatory. 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 have a daily stand-up with the students as well as arrange common lunches and workshops where the students and supervisors can learn from each other.
For more information please contact Joe Garrett.
https://www.ntnu.no/ansatte/joseph.garrett