This chapter introduces the reader to finite impulse response (FIR) and infinite impulse response state estimates, discusses cost functions and the most critical properties, and provides a brief historical overview of the most notable works in the area. It deals with some stochastic dynamic system or process and want to predict its further behavior, we need to know the system characteristics at the present moment. The state estimator performance depends on a number of factors, including cost function, accurate modeling, process suitability, environmental influences, and noise distribution and covariance. An exception is white Gaussian processes, where the block noise covariance matrices are diagonal and the Kalman recursions exactly compute the batch optimal FIR estimates. The history of the development of methods of batch FIR state estimation related to filtering, smoothing, and prediction is rooted in a wide area of estimation theory.
Introduction
2022-08-09
24 pages
Article/Chapter (Book)
Electronic Resource
English
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