Coordinated Planning between a satellite constellation and a Autonomous Surface Vehicle
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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
Coordinated Planning between a satellite constellation and a Autonomous Surface Vehicle (F25/S26)
Project Description
Since 2021, NTNU has participated in a field campaign in Frohavet, directly west of Trondheim. NTNU manages different sensors that are part of the so-called operational pyramid which has taken part in these missions. The HYPSO satellites record images of hthe target
In the observational campaigns, these instruments are deployed and managed through mission planning and data collection and analysis. HYPSO-2 is a Hyperspectral imagery that collects data over 120 bands. In situ data can be sampled by the Autonaut, an Autonomous Surface Vehicle (ASV). Integrating the mission planning of the instrument is pivotal to achieve synergy between the agents in the pyramid.
Tasks: Review on satellite-ground agent coordination Simulate the HYPSO-Autonaut case and analyse how to integrate mission plans for the use case, minimising data latency Develop strategies for jointly planning satellite imaging and USV paths.
Supervisor(s)
This project would be advised by Joe Garrett and co-supervised by PhD student Corrado Chiatante.