Applied State Estimation And Association

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Applied State Estimation and Association

Applied State Estimation and Association
Author :
Publisher : MIT Press
Total Pages : 473
Release :
ISBN-10 : 9780262034005
ISBN-13 : 026203400X
Rating : 4/5 (00X Downloads)

Book Synopsis Applied State Estimation and Association by : Chaw-Bing Chang

Download or read book Applied State Estimation and Association written by Chaw-Bing Chang and published by MIT Press. This book was released on 2016-07-08 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: A rigorous introduction to the theory and applications of state estimation and association, an important area in aerospace, electronics, and defense industries. Applied state estimation and association is an important area for practicing engineers in aerospace, electronics, and defense industries, used in such tasks as signal processing, tracking, and navigation. This book offers a rigorous introduction to both theory and application of state estimation and association. It takes a unified approach to problem formulation and solution development that helps students and junior engineers build a sound theoretical foundation for their work and develop skills and tools for practical applications. Chapters 1 through 6 focus on solving the problem of estimation with a single sensor observing a single object, and cover such topics as parameter estimation, state estimation for linear and nonlinear systems, and multiple model estimation algorithms. Chapters 7 through 10 expand the discussion to consider multiple sensors and multiple objects. The book can be used in a first-year graduate course in control or system engineering or as a reference for professionals. Each chapter ends with problems that will help readers to develop derivation skills that can be applied to new problems and to build computer models that offer a useful set of tools for problem solving. Readers must be familiar with state-variable representation of systems and basic probability theory including random and stochastic processes.


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