Vessel autonomy

In the coming years, autonomous shipping is expected to create a revolution in maritime navigation. In addition to large autonomous ships, there is a growing market for small/medium agile vessels, requiring new sensing capabilities to provide situational awareness of the surrounding environment. Their requirements differ considerably from those of large ships: (i) for the safety of the boat, humans or sea animals in/on the water, robust all-weather day/night detection and classification of small objects is required at ranges of up to ~300 m, which is too close for large ships to manoeuvre, (ii) large waves are more hazardous for smaller boats so wave profiling is critical for adaptation to the dynamic environment and safe path planning.

To address this, our Group is involved in a 3.5 year project which started in April 2020 in partnership with the radar group at the University of Birmingham. The project is named Sub-THz Radar sensing of the Environment for future Autonomous Marine platforms (STREAM). The goal for the project is to develop novel solutions for marine autonomous sensing using sub-THz radars operating in the 140-340 GHz frequency spectrum. Using such short wavelengths with high bandwidth enables greater radar image quality, better resolution (both range and cross-range) for high fidelity target detection and classification, and better sensitivity to surface texture for anomaly detection. The research programme includes:-

  1. Experimental trials in the UK to gather extensive sea-surface data with various radars ranging from 24-700 GHz frequency bands, at different sea states. Along with sea-surface data, radar data for various relevant targets (sea mammals, buoys, swimmers etc.) will also be collected.
  2. Determining scattering properties (radar cross section (RCS) and spatio-temporal variations) of sea-surfaces and other targets by using both modelling and analysing experimental data.
  3. Investigating propagation in the marine boundary layer at sub-THz frequencies, addressing the current lack of knowledge in this area.
  4. Analysing the radar data for anomaly detection algorithm development.
  5. Investigating waveform diversity to enable cognitive adaptivity of the radar sensor.
  6. Assess the viability of future sub-THz radar sensor architectures based on the results obtained from modelling predictions and experimental data analysis.

Researchers: Dr Samiur Rahman, Mr Aleks Vattulainen & Dr Duncan A. Robertson.

Project funding: EPSRC, EP/S033238/1, 2020-2024.