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Welcome to University Defence Research Centre

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.

The main mission of UDRC is to maintain the global leading position of UK in defence related signal processing research and applications. In order to achieve this, UDRC is aiming to promote fundamental research in signal processing and related areas, particularly with application to defence related industry. At the same time UDRC aims to provide a forum to invite and engage signal processing researchers from academia, industry and government to tackle open but significant challenges in the field.

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.

Research Themes

The research projects in UDRC have been grouped in the following 4 technical Themes.

Classification and Multimodal Processing
Supper resolution Source Separation
Distributed Signal Processing
Non Conventional Signals

News and Event highlight

SSPD 2011 - Registration Open

The registration for the 2nd Sensor Signal Processing for Defence (SSPD 2011) Conference is now open. To register, please visite the SSPD 2011 website.

The 2nd Sensor Signal Processing for...

Research Challenges

The main research focus and challenges of the UDRC are:

Array Signal Processing
Radar, Sonar and Audio Signal Processing
Signal Processing for Security
Multimodal Signal Processing
Sensor Fusion
Image and Video Classification
Distributed Signal Processing for Wireless Sensor Networks
Signal Processing for Communications

Latest publications

Harry Commin and Athanassios Manikas The Figure of Merit "C" for Comparing Superresolution Direction-Finding Algorithms
2010
Duncan P. Williams, Gary L. Davies, Andrew J. Evans Using context to detect underwater objects
2010
Dahir H. Dini, Danilo P. Mandic Analysis of the Widely Linear Complex Kalman Filter
2010
Murat Uney, Simon Julier, Daniel Clark, Branko Ristic Monte Carlo Realisation of A Distributed Multi-Object Fusion Algorithm
2010
Adrian Brown, Samantha Dugelay, Duncan Williams, Shannon Goffin Feature Extraction for Early Auditory-Visual Integration
2010

Latest News

Research Spotlight

[O01] Locally Invariant Signal Processing to Discriminate Between Key Man-made and Natural Features

A popular approach for automatic minehunting with sidescan sonar is to focus on shadow regions of objects. This is thought by many as more dependable than the highlight region. In good conditions, and given prior knowledge, it can be used to accurately classify the object into broad shape classes. However, under changing conditions, and in the presence of clutter such as sand ripples, this simplified approach tends to lose its effectiveness. The highlight region of objects has also been considered for classification but so far results have proven to be too dependent on the specific sonar...

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