MSc Communications and Signal Processing

Year of entry: 2024

Course unit details:
Multi-Sensor Signal Processing & Imaging

Course unit fact file
Unit code EEEN64442
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Available as a free choice unit? No


  • Introduction to sensor fusion for multi-sensor systems and tomography imaging
  • Hard-field tomography: x-ray, gamma-ray, optical and terahertz tomography. Sensing principles. Introduction to algorithms for hard-field reconstruction. Software design. Hardware design: sources, detectors and measurement “train”. State-of-the-art in hard-field process tomography. Multi-sensor, multi-modality approach.
  • Soft-field tomography: electrical impedance and capacitance tomography, electromagnetic tomography. Sensing techniques. Hardware design: sensors, measuring circuits and calibration. Soft-field reconstruction and software design, applications. State-of-the-art in soft-field process tomography.




This course unit detail provides the framework for delivery in the current academic year and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.

The programme unit aims to:

  • Introduce students to theoretical and practical fundamentals of signal and data processing for multi-sensor systems, addressing in detail the underlying principles, measurement techniques, image reconstruction and system design the example case of tomography imaging.
  • Introduce students to the various aspects of multi-sensor data fusion for tomography imaging applications: medical, industrial, security.
  • Enable students to undertake simple designs of multi-sensor and tomography imaging systems.
  • Prepare students for Research and Development (R&D), academic or other employment in this area

Learning outcomes

On the successful completion of the course, students will be able to: Developed Assessed

Analyse the industrial needs and match them with existing technology; identify the needs for development of new technology and the basic drivers and developments in industrial multi-sensor systems.

ILO2 Describe the physical and engineering principles of instrumentation for hard-field and soft field imaging. X X
ILO3 Perform conceptual designs of simple multi-sensor tomography systems. X X
ILO4 Define the inverse problem in a particular imaging scenario as an approach to sensor fusion. X X
ILO5 Perform back projection image reconstructions for soft field and hard field. X X
ILO6 Identify the motivation for multi-sensor fusion and the value of tomography imaging. X  


Teaching and learning methods

Lectures, Pre-recorded videos, Tutorials, Practical Work/ Laboratory and Private Study

Assessment methods

Method Weight
Written exam 70%
Written assignment (inc essay) 30%

Recommended reading

Kak, Avinash C. (Avinash Carl),Principles of computerized tomographic imaging, IEEE Engineering in Medicine and Biology Society. Conference. Type: Book ISBN: 0879421983 Available At: Main Library Blue Area Floor 3 616.0757 KAK

Computed tomography fundamentals, system technology, image quality, applications

Kalender, Willi A. Type: Book ISBN: 9783895786440 Edition: 3rd ed.

Measurement Science and Technology, Volume 17, Number 8, August 2006

K.J. Binns, P.J. Lawrenson, C.W. Trowbridge, The analytical and numerical solution of electric and magnetic fields: Wiley 1992

Jianming Jin, The finite element method in electromagnetics: John Wiley & Sons 3rd ed. (2014)

Study hours

Scheduled activity hours
Lectures 24
Practical classes & workshops 9
Tutorials 9
Independent study hours
Independent study 108

Teaching staff

Staff member Role
Krikor Ozanyan Unit coordinator
Wuliang Yin Unit coordinator

Return to course details