Signal Processing for a Networked Battlespace

This research is carried out under the Unversity Defence Research Collaboration (UDRC) funded by the MOD and EPSRC.

The UDRC is a collaborative research project with the work being carried out by two Consortia. Edinburgh Consortium is made of the University of Edinburgh, Heriot-Watt University and The Queen's University of Belfast. LSSCN Consortium is made up of Loughborough University, University of Surrey, University of Strathclyde, Cardiff University and Newcastle University.

 

Phase 2 of the programme; Signal Processing in a Networked Battlespace will deliver integrated multi-sensor systems as well as limiting data overload and maximizing data relevance within the network, through novel acquisition, processing and sensor management.The UDRC provides MOD with direct access to an academic signal processing talent pool deployable on MOD problems at short notice. Twenty researchers in the UDRC have Security Clearance (SC) and a further two have Developed Vetting (DV) clearance.

The Research work will investigate some of the following challenges. More information on the research can be found on the project website.

  • Weak signal detection in high volume of clutter
  • Signal processing in high dimension feature space
  • Signal processing in high uncertainty
  • Time-series/High-volume Signal Detection
  • Signal processing for sparse or fleeting signals
  • Signal processing to support sparse sampling of highly non-stationary signals
  • Extraction/separation of multiple overlapping/interwoven signals
  • Statistical anomaly detection
  • Signal Processing in Novel Computation Architectures:
  • Distributed/decentralised signal processing:
  • Algorithms to support dramatic reduction in computation
  • Accreditable machine learning or data-driven techniques

 

 

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University Defence Research Collaboration

Project Website: 

Principal Investigator: 

Co-Investigators: 

Research Institutes: 

  • Imaging, Data and Communications

Research Themes: 

  • Institute for Digital Communications Themes
  • Communications
  • Signal and Image Processing

Last modified: 

Friday, May 14, 2021 - 11:28