Postgraduate research project

Distributed acoustic sensing for monitoring complex environments

Funding
Competition funded View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date

About the project

This project aspires to advance distributed acoustic sensing by developing physics-enhanced signal processing algorithms particularly suited for complex multi-source environments.

Distributed acoustic sensing (DAS) is a relatively recent technology offering continuous acquisition over kilometres of optical fibre from one location. This setup brings abundant data containing signals from various sources, such as:

  • people
  • vehicles
  • machinery
  • transportation
  • services

The most common practice in exploiting this data is listening for sound sources (looking for ‘hot spots’) or black-box machine learning. However, enhancing these approaches with an understanding of wave physics can unlock the full potential of DAS, which shows high potential as a crucial component of security-focused monitoring.

The key contributions of this project will include:

  • a rigorous determination of the strengths and limitations of different fibre configurations, including, the effect of cable design, conduits, installation, and proximity to infrastructure
  • building reliable models for DAS sensing of waves in complex media from various sources
  • developing imaging workflows for multiple source identification in complex environments
  • merging different modalities of optical fibre sensing to increase reliability

You will develop analytical and numerical models for wave propagation in the soil-cable systems and cables themselves to capture the fundamental physics behind sensing. Later in the project, the focus will include additional complexities such as infrastructure, tunnels or foundations.

Complemented by experimental measurements and their analysis, You will establish firm foundations for enhancing the interpretation of DAS data and inform machine learning processing algorithms.

The Centre for Doctoral Training in Complex Integrated Systems for Defence & Security (CISDnS) is committed to promoting equality, diversity and inclusivity. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break or are transitioning into a new role. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance.