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Computer Vision and Artificial Intelligence for the detection and tracking of small UAVs PhD

  • Full or part time
  • Application Deadline
    Friday, June 26, 2020
  • Funded PhD Project (UK Students Only)
    Funded PhD Project (UK Students Only)

Project Description


This exciting funded PhD opportunity exists in the area of computer vision and artificial intelligence to tackle an increasing threat to aviation security by small UAV intrusions through the use of novel techniques and algorithms.

Although drones have been in use for several years, most of the research has focused on their design, development and functionality to improve manoeuvrability. However, now the objective has reversed and we require sophisticated systems to detect and track small drones. This research will focus on the autonomous/intelligent detection and tracking in close proximities with a specific objective of security of airports and assets within.

The project focuses on both, the software and the hardware aspects. The focus is on computer vision and artificial intelligence where deep learning will be employed to design vision-based intelligent/autonomous system with advanced algorithms and system integration with multiple sensors for better decision making.

This project requires someone with excellent computer programming skills in the above mentioned areas (preferably C++, Python and OpenCV, Kerras, PyTorch, TensorFlow etc). You must have a hands-on approach as you will be developing the intelligent algorithms as well as implementing them on cameras (and perhaps other sensors), testing them at the new “Drone Corridor” being built at Cranfield University and integrate the system with the holographic radar system.

Cranfield is an exclusively postgraduate university in technology and management. Cranfield is recognised for delivering outstanding transformational research that meets the needs of business, government and the wider society. The Department of Transport, through the FASS programme, offers an opportunity to the industry and Cranfield University to collaborate to create novel solutions to the future aviation industry. In this project, two industrial partners will be supporting your research.

This project will offer exceptionally accurate detection and tracking of small drones flying near the airports hence allowing smooth and continuous operations of current and future aviation industry and frictionless movement of people and goods. The vision-based system will need to integrate with the holographic radar system provided by one of the industrial partners in this project.

You will be a member of Centre for Computational Engineering Sciences and will be based at the DARTeC which is a £65 million new research centre focused on the “Aviation of Future”. Cranfield is also setting up 16 km long national facility for drone flights (referred to as drone corridor) which will be extensively used for experimentation in this project. With the industrial collaborations with major radar manufacturer, you will have the opportunity to spend time with our industrial partners and learn from the professionals working on the development of cutting edge technologies. You will be able to disseminate your research through conferences and journal publications.

This is a very exciting project for a suitable candidate where you will be exposed to latest technological developments, learn from the industrial and academic experts working in this area and prepared for an exciting career in academia or industry.


Funded by the Department for Transport, Cranfield University and our Industrial collaborators, this studentship will provide for a home student a maintenance bursary of £18,000 pa (Tax Free) plus fees for three years. The student will also have the opportunity to travel for conferences and meetings with industrial collaborators.

Entry requirements

Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit someone with a strong background in computer programming, hands-on approach to systems integration and out of the box thinking ability and engineering skills.

How to apply

If you are eligible to apply for this studentship, please complete the online application form by clicking on ’Visit Website’.

For further information please contact:

Name: Dr Zeeshan Rana
T: (0) 1234 750111 Ext: 8216

Funding Notes

Click on ’Visit Website' for further funding details.

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