Loughborough University Featured PhD Programmes
Sheffield Hallam University Featured PhD Programmes
Loughborough University Featured PhD Programmes

Machine Learning in Cognitive Radar for enhanced detection and tracking


Department of Electronic, Electrical and Systems Engineering

About the Project

This project is funded by the EPSRC’s I-CASE scheme and BAE Systems. The over-arching aim of the programme is to develop the next generation of signal processing algorithms that will push the limits of radar situational awareness in challenging operating environments beyond what is currently achievable.

Specifically, we focus on cognitive radar architectures, which are a drastic departure from the way conventional radar systems work. The key to unlock their full potential is the ability to “perceive” their operating environment from radar echoes they receive, and use that perception to maximise their detection and tracking performance by adjusting their transmit, receive or signal processing parameters to suit. To be able to perform these tasks is of tremendous value to radar capability and especially in detecting small vessels in dynamically changing sea conditions, but to facilitate them there is an underpinning fundamental problem. An optimal action by the radar is determined by an optimal perception of its environment, but the disturbances in a radar echo signal are random and highly variable. This necessitates the use of advanced algorithms for enhanced perception, as well as algorithms to determine adaptive rules of behaviour that drive the radar’s action. A solution with exciting possibilities is machine learning, but in-depth studies of how it may be incorporated in complex radar environments such as this and what its radar performance improvement is are yet to come forward, and this PhD project will address that.

Thus, the objectives of the PhD programme are to:
• Investigate the application of machine learning algorithms in cognitive radar architectures to create a dynamic perception of the operating environment
• Investigate adaption of radar waveforms and signal processing based on the dynamic environmental perception in order to optimise detection and tracking.
• Develop the appropriate simulation environment to confirm theoretical understanding and assess the resulting performance
• Design and conduct a proof-of-concept experimental campaign to verify theoretical findings in a controlled environment

The project is ideally suited to graduates with a good quality earlier degree in Electrical Engineering, Physics or similar subject. The successful candidate will conduct their research at the Microwave Integrated Systems Laboratory at the University of Birmingham, which comprises some 30 researchers on radar technologies and has a suite of state of the art radar testing facilities and instrumentation. Additionally, the student will spend time at BAE Systems at the Isle of Wight to receive a more complete training experience and acquire skills directly linked to industry to complement their research skills. The studentship covers home tuition fees and a standard stipend, along with funding to spend time a BAE Systems premises and to attend international conferences.

For enquiries, please contact Prof. Chris Baker () or Dr. Mike Antoniou ().


Funding Notes

Funding note:

As the candidate will work at and with BAE Systems, the post is open to UK nationals only, and subject to obtaining security clearance. Start time: Early January 2021 at the latest.

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here

The information you submit to University of Birmingham will only be used by them or their data partners to deal with your enquiry, according to their privacy notice. For more information on how we use and store your data, please read our privacy statement.

* required field

Your enquiry has been emailed successfully



Search Suggestions

Search Suggestions

Based on your current searches we recommend the following search filters.



FindAPhD. Copyright 2005-2020
All rights reserved.