The Kalman filter which is over 50 years old is one of the most important and common data fusion algorithms in use today. It combines measurements and predictions over time to produce accurate estimates of unknown variables. It can be used in any dynamic system where information is uncertain or continuously changing, and its computational requirements are quite small. For this reason the Kalman filter is still in use and has numerous applications in Engineering, Physics, Computer Science, and Biology amongst other fields.In this talk I will explain the basis of this algorithm via a simple and intuitive derivation, and discuss some of its many different uses.
Details about the programme of seminars organised by SMSAS postgraduate research students for SMSAS postgraduate research students.