Overview
What you will study
The aim of this Sensor Fusion - Architectures, Algorithms and Applications course offered by Cranfield University is to acquaint you with the basic principles of estimation theory, and critically understand the pros and cons of filtering and fusion theories when applied to the problem of sensor fusion.
On successful completion, you will be able to:
- Demonstrate the nature, purpose, and design procedures of estimation theory and sensor fusion
- Critically understand challenging problems in the conventional estimation and sensor fusion approaches
- Critically select and apply an appropriate filtering technique and sensor fusion method to a specific problem depending on the types of system/sensor dynamics and noise characteristics.
Programme Structure
The program focuses on:
- Estimation theories and sensor fusion
- Statistical analysis
- Observers
- Estimators
- Sensor integration architectures
- Multiple sensor fusion
Key information
Duration
- Full-time
- 8 days
Start dates & application deadlines
- StartingApply anytime.
Language
Delivered
Campus Location
- Cranfield, United Kingdom
Disciplines
Industrial & Systems Engineering View 25 other Short Courses in Industrial & Systems Engineering in United KingdomWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This course is ideal for engineers with interest in estimation theories, sensor fusion and their architecture, algorithms and applications.
Tuition Fees
-
International Applies to you
Applies to youNon-residents1800 GBP / full≈ 1800 GBP / full -
Domestic Applies to you
Applies to youCitizens or residents1800 GBP / full≈ 1800 GBP / full
Living costs
Cranfield
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.