Master of Engineering (MEng)

MEng Electrical and Electronic Engineering with Industrial Experience

*This course is now closed for applications for 2025 entry.

  • Duration: 5 years
  • Year of entry: 2025
  • UCAS course code: H601 / Institution code: M20
  • Key features:
  • Industrial experience
  • Scholarships available
  • Accredited course

Full entry requirementsHow to apply

Course unit details:
Multi-Sensor Signal Processing & Imaging

Course unit fact file
Unit code EEEN44441
Credit rating 15
Unit level Level 4
Teaching period(s) Semester 2
Available as a free choice unit? No

Overview

  • 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. 
  • MRI principles, imaging methods and applications. 

Aims

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 successful completion of the course, a student will be able to:

ILO 1: Perform back projection image reconstructions for soft field and hard field.

ILO 2: Perform conceptual designs of simple multi-sensor tomography systems.

ILO 3: 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.

ILO 4: Define the inverse problem in a particular imaging scenario as an approach to sensor fusion.

ILO 5: Identify the motivation for multi-sensor fusion and the value of tomography imaging.

ILO 6: Describe the physical and engineering principles of instrumentation for hard-field and soft field imaging.

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%

Feedback methods

.

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 6
Tutorials 9
Independent study hours
Independent study 111

Teaching staff

Staff member Role
Wuqiang Yang Unit coordinator
Anthony Peyton Unit coordinator

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