This text set of lecture notes presents the material from a second semester graduate level course on estimation offered in the Dept. of Electrical and System Engineering at the U. of Connecticut. The main goal of the course is to convey the knowledge necessary for the evaluation and design of state estimators that operate in a stochastic environment. The material covers the topics usually taught in control-oriented EE/systems and aeronautical engineering programs. The prerequisites are a solid knowledge of linear systems and probability theory at the first semester graduate level. Annotation copyright Book News, Inc. Portland, Or.
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This text is designed for applied researchers and design engineers in civil and military systems. It should also be suitable for graduate students in control systems, aerospace systems and robotics. The book provides engineering tools necessary for the design and evaluation of state estimators in stochastic systems, with guidelines for the selection of estimator design parameters. It includes DynaEst 2.0, an interactive design tool for Kalman filters and an adaptive multiple model estimator.
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