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| Location: | Cranfield / United Kingdom / View location on map ▾ Hide location on map ▴ | ||
| Duration: | 12 months | Start Date: | September |
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| Languages: | English | ||
Suitable for graduates working within government or industry who wish to broaden their understanding of defence sensor systems and the integration and data fusion techniques employed to maximise the effectiveness of multi-sensor systems.
Takes you on to a thorough understanding of the principles and technology of sensors, methods of sensor integration and data fusion with applications to weapon integration.
You will be taught by faculty from the Defence Academy - College of Management and Technology, many of them world leaders in their field, who understand the problems of translating theory into practice. The defence-specific content will be delivered by military staff from the Defence Academy of the United Kingdom. Visiting lecturers include experts from industry, research establishments and Government departments, particularly the MOD.
The past decade has seen major developments in sensors and in data fusion and integration techniques used to maximise data retrieval from multi-sensor systems.
The application of these techniques to weapons systems has so far been selective, but with the emphasis on smaller, more technological armies, multi-sensor systems are expected to play a crucial role in electronic warfare and guided weapon domains. For example, the Technology Foresight Review highlighted the importance of sensors for the future generation of weapon systems and it is estimated that, of future investment in guided weapons, over half will be in the field of sensors.
Also, the use of multiple surveillance sensors on a variety of platforms ranging from unattended ground sensors to space-borne assets will provide the future ISTAR capability for intelligence and surveillance. The use of state-of-the-art data fusion technology which maximises information extraction from such sensors is essential to meet the future needs of the ISTAR domain within a network enabled capability. This key role of data fusion has been highlighted in the Defence Technology Strategy.
Furthermore, the use of multiple sensors and data fusion extends beyond purely the defence domain with applications in, for example, the automotive industry and security systems. The course will also provide a solid foundation for those interested in these non-defence areas.
Modules: Foundation modules
The foundation level modules are designed to provide the groundwork in mathematics and science required for the course:
* Mathematics and Signal Processing
* Propagation Theory and Antennas.
Subject modules
The subject level modules deal with sensor technology:
* Radar Principles
* Electro-Optics/Infrared Sensors (Part One)
* Sonar/Acoustic/Seismic Sensors
* Sensor Fusion
* Soft Computing and Optimisation
* Data and Information Fusion
* Analysis and Design of Search and Track Radar
* Practical Radar Systems
* Electro-Optics/Infrared Sensors (Part Two).
System modules
The system level modules concentrate on systems integration and data fusion, together with a project:
* Sensor Integration and Data Fusion Study
* Individual Project.
Each module has an entry pack that specifies the knowledge required to study the module and an exit pack consisting of an assignment which is assessed. The project will commence at the University, but can be carried out in industry under the supervision of a University supervisor and an industrial mentor.
You are normally required to take an English Proficiency Test.
Most European Universities recognise the IELTS test.
Take testNormally a 1st or 2nd class honours degree (or equivalent) in science, engineering or maths. Alternatively, a lesser qualification together with appropriate work experience may be acceptable. Students whose first language is not English must attain an IELTS score of 7.
| Minimal degree required: | Bachelor's degree |
| Minimal amount of work experience | Not specified |
| IELTS Band: | 7.0 |
| Cambridge English: Advanced (CAE): | Grade C (Score: 60) |
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