Sensors Group

For further information please contact

Dr Mark Richardson.
Head of Sensors Group

T: +44 (0) 1793 785230

E: mailto:m.a.richardson@cranfield.ac.uk

 

Call for Papers

PhD research opportunities in the Sensors Group download pdf

All research opportunities at Cranfield Defence and Security

 

The Sensors Group’s interests cover a wide range of sensors across the Electromagnetic Spectrum ranging from VHF to mmW Radar through far-IR to UV Spectroscopy. Research into Automatic Target Recognition, Difficult Target Detection, Radar Waveform Optimisation, mmW properties of materials, Hyperspectral and Broadband Imaging is also conducted.

The research interests cover not only the above fields but also allied topics concerned with Sensor Fusion, such as, Evolutionary Optimisation, Image Processing for Radar, E/O, IR and UV, cooperative guidance of missiles and UAVs and Missile Homing Systems (Radar, IR and E/O).

Additionally the Group also offers

Laboratory Facilities

  • Anechoic chamber for measurements in the Giga hertz range
  • Vector Network Analyser to 110GHz
  • Performance measurement of transmitters and receivers
  • UV to far-IR Spectroscopy
  • Hyperspectral and broadband imaging
  • Simulation
  • Instrumentation and prototyping
  • Professional consultancy

Our expertise includes

  • Surveillance
  • Target Acquisition
  • Pre and Post Detector Processing
  • Counter Measures and Protective Measures
  • Instrumentation
  • Hyperspectral Imaging
  • Environmental measurements using Ground Based Synthetic Aperture Radar
  • MPRF Radar Waveform Optimisation
  • Low RCS Target Detection
  • Measurement of mmW properties of Dielectric Materials
 

Staff

Dr Mark Richardson, Head of Group

Dr Jimmie Aitken

  • Radar Lecturer

Dr Clive Alabaster

  • mmW Dielectric Measurements
  • Waveform design and optimisation of PRF set selection for MPRF pulse Doppler radars

Dr Nabil Aouf

  • Image Processing
  • Sensor System Optimisation

Dr John Coath

  • EO/IR Lecturer

Dr Evan Hughes

  • Evolutionary algorithms applied to Many-Objective optimisation, on-line and noisy systems.
  • Automatic Target Recognition in Radar images
  • Medium PRF Radar waveform design, MPRF radar processing methods, Novel CFAR systems, detection and tracking of low-observable targets;
  • Multiple hypothesis target tracking,
  • Stochastic estimation techniques
  • Cooperative guidance.

Dr David James

  •  Laser DEW
  • EOPM

Mr Mike Lewis

  • Radar Lecturer

Mr Ian Luckraft

  • EO/IR Lecturer

Dr Keith Morrison

  • SAR
  • Ground Based SAR for Environmental Measurements.
  • Noise Radar

Dr Ivor Morrow

  • Dr. Morrow is a research active Senior Lecturer and Leader of the Laboratory of Electromagnetic Research.

Mr Roger Picton

  • Radar Lecturer

Dr Peter Yuen

  • Hyperspectral Imaging
  • Data Mining applied to the accurate and efficient classification of High Dimensional Image Data.

Izzati Ibrahim

 

PhD Students

R Birchenall

  • Development of Pre-Emptive Countermeasures against IR Manpads.

T Chen

  • Remote assessment of intent by hyperspectral sensing of human physiological responses triggered by stress

Nathan Clow

M Elson

K Hong

  • Exploitation of spectral and textural information for the detection of anomalous behaviour in a cluttered background

J Jackman

  • The modelling and simulation of pre-emptive countermeasures

H Kam

  • Assessment of improvements to classification accuracy that can be achieved by an adaptive feature selection scheme

K Hong

S Imram

B Kellaway

  • Assessment of the Burst Illumination Laser for the Identification of Military targets

M Kharbat

  • Robust visual guidance applied to spacecraft

G Marino

  • Limits of Automatic Target Recognition

A Nemra

  • Robust Airborne 3D Visual Simultaneous Localization and Mapping

I Parker

G Pellowe

D Rodriguez

M A Shah

  • Cooperative Perception and Cooperative Path Planning for a Group of UAVs in a Dynamic Environment

M Stevenson

  • Evolutionary Many Objective Optimisation

U Soori

A Tsitiridis

  • Object recognition and tracking using cortex like machine vision processing