PhD Studentship: Passive RF tomography for early wildfire detection in forested environments

Climate change is driving more frequent and severe wildfires in the UK and globally. Even small ignition events can escalate rapidly, yet many landscapes still lack affordable and continuous monitoring. Conventional early-warning systems, such as optical/IR cameras, satellites, human observers, and dense sensor networks, either provide limited warning time, depend on clear visibility, or are too costly to deploy at scale. This leaves a critical capability gap in wildfire early detection.

This PhD will explore a novel solution: using ambient Radio Frequency (RF) signals as passive environmental probes. The proposed system will use Signals of Opportunity (SoO), such as TV and radio broadcasts, cellular networks, and other existing transmitters, to detect small perturbations in the RF propagation channel caused by wildfire effluents. Inspired by passive radar principles, this approach could enable low-cost, wide-area coverage without the constraints of optical visibility.

The PhD will develop RF propagation models that incorporate the effects of fire effluents, validated through controlled experimentation. You will develop tomographic inversion methods and anomaly-detection algorithms capable of separating fire-induced signatures from natural environmental variability (weather, canopy changes, tree motion) and fluctuations in the SoO sources themselves. Machine-learning methods will help improve long-term robustness and minimise false alarms.

A good understanding of electromagnetics, RF propagation, signal processing, and machine learning would be beneficial. This project offers a unique opportunity to help establish the scientific basis for a potentially transformative climate-adaptation technology.

Primary supervisor: Dr Chinthana Panagamuwa

Secondary supervisor: Dr Kostas Kyriakopoulos

Entry requirements:
Students should have, or expect to achieve, at least a 2:1 degree qualification in Electronic or Communications Engineering

English language requirements:
Applicants must meet the minimum English language requirements.

Funding information:
The studentship is for 3 years and provides a minimum tax-free stipend of £ 20,780 per annum (2025/26 rate) for the duration of the studentship plus university tuition fees.

Funding will be awarded on a competitive basis and is not guaranteed; availability will depend on the outcome of the selection process and subject to final approval by the University.

The following selection criteria will be used by academic schools to help them make a decision on your application: https://www.lboro.ac.uk/study/postgraduate/apply/research-applications/studentship-assessment-criteria/.

How to Apply:
All applications should be made online. Under programme name, select Electronic, Systems and Electrical Engineering. Please quote the advertised reference number: FP-SA26-CP in your application.

Applications must include a personal statement, up-to-date curriculum vitae (CV), details of two referees (one from your highest degree qualification), certified certificates and transcripts for all completed degree programmes, and a reference to the project FP-SA26-CP. Submission of a Research Proposal is not essential but may strengthen your application. Incomplete applications received after the closing date may not be considered for interview.

Shortlisted candidates will be contacted for an interview, which are expected in February/early March 2026.

Advert information