Simulations Using the Kalman Filter

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" Simulations Using the Kalman Filter "
Vascimini, Vincent G. Chan, Kit

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1114216
Doc. No	:	TLpq2404633855
Main Entry	:	Chan, Kit
	:	Vascimini, Vincent G.
Title & Author	:	Simulations Using the Kalman Filter\ Vascimini, Vincent G.Chan, Kit
College	:	Bowling Green State University
Date	:	2020
student score	:	2020
Degree	:	M.A.
Page No	:	55
Abstract	:	Control and estimation theory are branches of mathematics that involve using data and measurements to estimate the value of a parameter of interest, and how changing certain parameters effects this estimation. The Kalman filter is a fundamental result in control and estimation theory that was introduced by Rudolf E. Kalman in 1960. The Kalman filter is a set of equations that provides an optimal estimate of the state of a system in a least-squares sense. The filter is often sought for its recursive and noise-smoothing properties, and has been found useful across many disciplines and in real world systems. This thesis will contribute to the literature of control and estimation theory by providing an introduction to the principles of the filter. This introduction includes a brief history of the filter, a derivation of the filter equations, and simple examples of applications of the filter.
Subject	:	Control theory
	:	Estimation theory
	:	Filter derivation
	:	Functional analysis
	:	Kalman filter
	:	Simulations