Introduction

Signal Processing is fundamental to the capacity of all modern sensor/weapon systems. The University Defence Research Centre (UDRC) is concerned with fundamental research in Signal Processing with emphasis given to areas that play a substantial role in improving the performance of defence systems. These are:

 

  • Auto-calibration: Signal processing technologies that allow sensor arrays to be calibrated or recalibrated whilst in-use. These technologies will help to facilitate low cost, low-maintenance systems. They include compensating for variations in both the positions and the electronic characteristics of the sensors (including the equalisation of receiver channels) all of which can change with time.
  • Broadband signal separation: Signal processing technologies that separate broadband signals received at a sensor array into the signals from individual targets, enabling correct detection, classification and localisation (DCL) of multiple simultaneous targets. Subsets of this technology are conventional, adaptive, semiblind and blind broadband signal separation technologies. These technologies are also essential in communications systems.
  • Detection: Signal processing technologies that detect when received signals contain contributions from a target, particularly against a background of clutter (or reverberation) and interference.
    Classification: Signal processing technologies that identify or categorise targets.
  • High-resolution localisation: Signal processing technologies that yield more accurate target bearing estimates (and, where relevant, range estimates) than conventional localisation techniques, in particular when targets are close together in angle and/or range.
  • Multipath mitigation: Signal processing technologies that enable the detection, classification and localisation (DCL) of targets in the presence of multipath. Multipath is the term used to describe signals which appear to come from multiple directions due to echoes/reflections off large objects. Multipath can render classic DCL systems ineffective.
  • Low size, weight and power: Signal processing technologies that enable the use of hardware of reduced size, weight and power (SWAP). Typically they enable low SWAP processing hardware, but more innovative technologies may also enable low SWAP sensor hardware.
  • Non-stationary processing: Signal processing technologies which enable the DCL of fleeting or rapidly manoeuvring targets, or using non-rigid sensor arrays.


Currently there are 30 research projects running in the centre. From these, 17 come from the EPSRC-DSTL Open Call, 6 from the Core Research at Imperial College and 7 are DSTL Internal research project. More specifically the following projects are part of the MOD-UDRC.

DSTL - EPSRC Open Call Research

Code Principal Investigator Project
O01 Nick Kingsbury, University of Cambridge Locally Invariant Signal Processing to Discriminate between Man-Made and Natural Features
O02 Daniel Clark, Heriot-Watt University
 Generic Distributed Target Tracking Algorithms in Sensor Networks
O03 Alessandro Astolfi, Imperial College
 Hamiltonian-Based Cluster-Tracking and Dynamic Classification
O04 John Soraghan, University of Strathclyde
Advanced High Resolution Methods for Radar Imaging and Micro-Doppler Signature Extraction
O05 Kai-Kit Wong, University College London
Cooperative Localisation: Distributed Optimisation with Hypothesis Testing
O06 Michael Davies, University of Edinburgh
Source Separation for Electronic Surveillance
O07 Mathini Sellathurai, Queen's University Belfast
 Reducing the Clutter Competition in Forward Looking Radar
O08
 Bernard Mulgrew, University of Edinburgh
Distributed Signal Processing for Distributed Sensor Networks
O09 Rodrigo C. de Lamare, University of York
Low Complexity Adaptive Beamforming Algorithms
O10 Michael Davies, University of Edinburgh SAR Processing with Zeroes
O11 Wenwu Wang, University of Surrey
Multi-Modal Blind Source Separation for Robot Audition
O12 Yu Gong, University of Reading
Real Time Model Adaptation for Non-Stationary Systems
O13 James Hopgood, University of Edinburgh
Joint Blind Enhancement and Passive Source Localisation of Acoustic Signals
O14 Jinho Choi, Swansea University
 Distributed and Iterative Processing for Wireless Sensor Networks and Multiple Local Fusion Centres
O15 David Bull, University of Bristol
Scalable Information Fusion: Adaptivity for Complex Environments & Secure Data
O16 Yvan Petillot, Heriot-Watt University
 Target Detection in Clutter for Sonar Imagery
O17 Karl Woodbridge, University College London Classification and Tracking using Acoustic Micro Doppler Signatures

 

Core Research (at Imperial College London)

Code Principal Investigator Project
C1 Athanassios Manikas Auto-Calibration
C2 Athanassios Manikas Arrayed MIMO RADAR
C3 Danilo Mandic Widely Linear Adaptive Processing of Noncircular Complex Signals
C4 Eric Yeatman Low SWAP Target Localisation and Spatio-Temporal Beamforming
C5 Tania Stathaki Real-Time Multi-Modal Person Tracking

 

Internal Research (at DSTL)

Code Principal Investigator Project
I1 Duncan Williams
Context-Driven Object ID
I2 Adrian Brown Early Auditory-Visual Integration
I3 Jonathan Locke Extracting Tones Which Vary in Frequency from Non-Gaussian Noise
I4 Jonathan Barker Multi-Beam SAR
I5 Timothy Clarke Synthetic Noise
I6 Jonathan Perry Wave Wakes
I7 David Nethercott Identification and Classification of Multiple LPI Radar Emitters for Electronic Surveillance

 

The above projects have been grouped to the following 4 technical Themes (Please click on the figure for more information)

UDRC Themes