- UCAS course code
- H601
- UCAS institution code
- M20
Master of Engineering (MEng)
MEng Electrical and Electronic Engineering with Industrial Experience
*This course is now closed for applications for 2025 entry.
- Typical A-level offer: AAA including specific subjects
- Typical contextual A-level offer: AAB including specific subjects
- Refugee/care-experienced offer: ABB including specific subjects
- Typical International Baccalaureate offer: 36 points overall with 6,6,6 at HL, including specific requirements
Course unit details:
Multi-Sensor Signal Processing & Imaging
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 | |
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Independent study | 111 |
Teaching staff
Staff member | Role |
---|---|
Wuqiang Yang | Unit coordinator |
Anthony Peyton | Unit coordinator |