Automation of model based estimation filters
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Model based estimation filters are widely used in the field of estimation. They are applied for various types of dynamic and measurement models. There are different ways of solving these model based state estimation problems. The different methods available are analyzed, giving a detailed discussion of the different levels of automation available. A model is proposed for obtaining a higher level of automation. In this thesis, the various problems, that are to be faced while making the model based state estimation problems automatic, are discussed. A solution is proposed for over coming these difficulties, which is supported by the results obtained.
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