PhD Studentship: Signal Processing Techniques for Quantum-enhanced Distributed Radar Systems

Distributed radar systems comprise a coherent network of spatially distributed sensors that can be independently transmitting, receiving, or both. By acting in unison, rather than in isolation, they can utilise temporal and spatial diversity whilst simultaneously exploiting shared, intelligent adaptive signal processing whose combined performance and resilience can easily exceed that of the sum of their parts.

Replacing conventional radar oscillators with their Quantum alternatives is possible and can drastically increase the hardware sensitivity of distributed radar systems. They introduce new limits to oscillator noise levels, and the ability to coherently observe radar targets for periods of time never possible until now. The challenge is to understand how to derive distributed radar signal processing techniques that take full advantage of these capabilities, in order to translate them into optimal radar performance.

The purpose of the PhD is to lay down theoretical and practical foundations for Quantum-enhanced, distributed radar signal processing techniques that maximise target Signal-to-Noise Ratio (SNR). The algorithms we will derive will be applied and tested in the context of target detection, allowing smaller objects to be detected further away, as well as target feature extraction, which is the stepping stone to reliable target classification at further distances.

This will be the first attempt at creating holistic Quantum-enhanced radar systems, complete with both advanced hardware and tailored signal processing that maximises its utility.

The PhD goal will be achieved through fulfilment of the following objectives:

1. Design and development of long dwell-time, distributed signal processing algorithms for improved target detection
2. Design and development of signal processing techniques for enhanced target feature extraction
3. Experimental validation and assessment of real performance limits

The algorithms we will derive will be theoretically designed, verified by simulation, and tested in the field using the ADvanced Radar Network (ADRAN) facility on the UoB campus as the experimental testbed. The basis of theoretical and practical performance assessments, as well as its comparison with conventional approaches, will be the SNR improvement that our algorithms can achieve, and how this improvement translates to key detection metrics (probabilities of detection/false alarm/detection range) as well as reliability in extracting target features.

The project covers UK tuition fees and the standard UKRI PhD stipend and it is co-funded by the Quantum Hub in Sensing, Imaging and Timing (QuSIT) and BAE Systems. The academic supervision team have a track record of more than 20 years each on distributed radar research. The project is aligned to our strategic priority of expanding our critical mass on distributed radar, which is currently supported by prestigious and large initiatives including QuSIT and a newly awarded Royal Academy of Engineering (RAEng) Research Chair on distributed radar systems. Finally, it will benefit from world-leading infrastructure uniquely suited to support the programme, i.e. a fully operational network of Commercial-off-the-Shelf (COTS) primary surveillance radars specially modified to support fundamental distributed radar research that is available on campus.

Funding notes:

Only Home (UK) students are eligible. Successful candidates will have an excellent background in Engineering, Physics or a related subject area (first class degree or equivalent). We invite applications from highly motivated individuals, able to master complex subjects and eager to undertake research in a system- level approach with both theoretical & experimental thrusts of activities, publish research papers & advance research as part of a team of researchers working in the area.

References:

https://www.birmingham.ac.uk/research/centres-institutes/research-in-electronic-electrical-and-systems-engineering/communications-and-sensing/microwave-integrated-systems-laboratory-misl/our-facilities/adran-facility

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