Decentralised data fusion
This is a three-day intensive course in the theory and application of decentralised data fusion (DDF) methods. The course is:
- aimed at professional engineers and research scientists wishing to acquire a practical knowledge of DDF principles
- covers essential methods in decentralised tracking and identification, communication in decentralised sensor networks, sensor and network management, sensor node and sensor network design
- emphasises the application of DDF methods on specific demonstrator systems, focusing on issues of interface and network design
- includes a series of lectures, together with practical computer-based laboratories aimed at demonstrating implementations, and
- based on industry courses previously given by staff of the ACFR.
Lecturer
Objectives
- The course aims to provide practical knowledge and skills for engineers and scientists wishing to employ and develop DDF systems.
- The course is mathematically advanced but emphasises practical implementations in ground and airborne sensor networks.
- A key feature of the course is the use of practical laboratory sessions, based on Matlab, in which DDF methods are implemented and evaluated by students.
Outcomes
- To provide students with the theoretical and practical skills necessary to design, implement and evaluate DDF algorithms.
Prerequisites
- This course is intended for practising control or systems engineers, advanced graduate students or equivalent. Students are expected to have prior experience with state estimation methods (equivalent to KC-1).
Syllabus
- Distributed Data Fusion Methods: Probabilistic methods in decentralised data fusion, information theory models, multi-sensor estimation. Laboratories: Data fusion with Bayes theorem, Multi-sensor tracking.
- Estimation and Communication: DDF systems, decentralised multi-target tracking, communication in decentralised systems. Laboratories: Decentralised multi-target tracking, Operation of sensor networks.
- Advanced Methods and Systems: Communication management, sensor management, decentralised navigation and control, decentralised picture compilation, large-scale networks. Laboratories: Decentralised sensor management, Large-scale networks.
- Course content (pdf document 32kb)
Enrolment/Timing
- This is a special course run only on request.
- The course can be run at a company/institute site, providing appropriate (PC) facilities are made available for laboratory work.
- This course has a maximum enrolment of 15 students.
- For more information, please contact us - see Enquiries.
Course materials
- Course materials consist of comprehensive course notes, slides used in course presentation, source code for laboratories, tutorials and tutorial solutions. Course material is provided in both printed hard-copy and in soft-copy (CD-ROM) form.
Name and password required for the following information (Instructions: Create a directory for the course. Place laboratory software modules in different directories. Instructions for laboratories is in zipped files.):
- Notes (pdf document 3.88MB)
- Slides (pdf document 3.64MB)
- Laboratory Software (pkzip file 1.74MB)



