Maritime Surveillance form Space: On-board ship-detection with an RGB camera on HYPSO2
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Project and Master Subjects 2026-2027
- GNSS-R: GNSS jamming and spoofing detection and localization from space
- GNSS-R: Maritime surveilance with GNSS-R
- GNSS-R/GNSS-RFI Embedded system and processing pipeline
- Software system for new smallsat camera systems
- Automatic gain control for RF front end on GNSS RFI satellite payload
- Deployment of a telescope onboard a CubeSat
- Maritime Surveillance form Space: On-board ship-detection with an RGB camera on HYPSO2
- Generalized onboard/internal command and messaging framework
- Define a CubeSat bus architecture for a GNSS RFI mission
- Energy Budgeting for Dynamic Targeting
- Dynamic image target generation for the HYPSO satellites
- Design and Testing of a Strobing Illumination System for an Underwater Hyperspectral Camera
- LEO SatCom Signals of Opportunity for positioning, navigation and timing (PNT)
- yr.no for GNSS: Real-time service providing GNSS interference coverage
- Past Projects
Maritime Surveillance from Space: On-board ship-detection with an RGB camera on HYPSO2
Project description
Images from the RGB-camera on NTNU's HYPSO-2 satellite can resolve ships, given the right conditions. We want to explore the utility of this.
The inerested student should look into work facilitating the detection and classification of water anomalies in HYPSO imagery, applied to the case of onboard detection of ships. This work will first be a methodical analysis of possible algorithms and AI methods for ship detection, before quantitatively establishing promising methods and analysing their applicability to HYPSO data and the scope of possible ship sizes. The established method or workflow may then be extended for running onboard HYPSO potentially targeting FPGA.
Impact
Space technology plays a crucial role in achieving various Sustainable Development Goals (SDGs) set by the UN. A GNSS-RFI-payload has the potential to allows us to detect and monitor water vessels at sea and localize GNSS inference sources originating from sea or land. This project target
- SDG9 Industry, innovation, and infrastructure. The outcomes have an innovative and commercial potential for industry and can contribute both to new space-based infrastructure and protection of existing critical infrastructure beyond GNSS.
- SDG16 Peace, justice and strong institutions. GNSS interference monitoring is important for protecting essential services and infrastructure, both on a national and international scale.
Tasks and expected outcomes
This project is at an early stage, so the concept, method, tests and analysis of data should be performed.
- Investigate detection methods.
- Deveop a model that can analyze already captured images and try detect the presence of ships.
- Suggest improvements to the instrument, processing pipeline and any co-observations to evaluate the utility (use) of this camera.
Who we are looking for
We are seeking a highly motivated final year student in Electronics or a related field with an interest in signal processing and data analysis.
How we work
The student will be part of the NTNU SmallSat lab, a lab which typically hosts 10-20 master's student per semester. At the NTNU SmallSat Lab we encourage collaboration and try to get our group to help each other. To facilitate this, we as well as arrange common lunches and workshops where the students and supervisors can learn from each other. In some project we also implement a development process.