A Simple Treatment For Suboptimal Kalman Filtering In Case Of Measurement Data Missing
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A Simple Treatment For Suboptimal Kalman Filtering In Case Of Measurement Data Missing
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Author : Guanrong Chen
language : en
Publisher:
Release Date : 1989
A Simple Treatment For Suboptimal Kalman Filtering In Case Of Measurement Data Missing written by Guanrong Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Approximation theory categories.
A very simple yet efficient treatment is suggested in this short note as a suboptimal Kalman filtering algorithm for the standard filtering process under the irregular environment where some measurement data information is missing. Convergence analysis for the proposed algorithm is given.
Robust Kalman Filtering For Signals And Systems With Large Uncertainties
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Author : Ian R. Petersen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Robust Kalman Filtering For Signals And Systems With Large Uncertainties written by Ian R. Petersen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
A significant shortcoming of the state space control theory that emerged in the 1960s was its lack of concern for the issue of robustness. However, in the design of feedback control systems, robustness is a critical issue. These facts led to great activity in the research area of robust control theory. One of the major developments of modern control theory was the Kalman Filter and hence the development of a robust version of the Kalman Filter has become an active area of research. Although the issue of robustness in filtering is not as critical as in feedback control (where there is always the issue of instability to worry about), research on robust filtering and state estimation has remained very active in recent years. However, although numerous books have appeared on the topic of Kalman filtering, this book is one of the first to appear on robust Kalman filtering. Most of the material presented in this book derives from a period of research collaboration between the authors from 1992 to 1994. However, its origins go back earlier than that. The first author (LR. P. ) became in terested in problems of robust filtering through his research collaboration with Dr. Duncan McFarlane. At this time, Dr. McFarlane was employed at the Melbourne Research Laboratories ofBHP Ltd. , a large Australian min erals, resources, and steel processing company.
Nonlinear Stochastic Control And Filtering With Engineering Oriented Complexities
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Author : Guoliang Wei
language : en
Publisher: CRC Press
Release Date : 2016-09-15
Nonlinear Stochastic Control And Filtering With Engineering Oriented Complexities written by Guoliang Wei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-15 with Mathematics categories.
Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for stochastic systems with traditional and emerging engineering-oriented complexities. The book begins with an overview of the relevant background, motivation, and research problems, and then: Discusses the robust stability and stabilization problems for a class of stochastic time-delay interval systems with nonlinear disturbances Investigates the robust stabilization and H∞ control problems for a class of stochastic time-delay uncertain systems with Markovian switching and nonlinear disturbances Explores the H∞ state estimator and H∞ output feedback controller design issues for stochastic time-delay systems with nonlinear disturbances, sensor nonlinearities, and Markovian jumping parameters Analyzes the H∞ performance for a general class of nonlinear stochastic systems with time delays, where the addressed systems are described by general stochastic functional differential equations Studies the filtering problem for a class of discrete-time stochastic nonlinear time-delay systems with missing measurement and stochastic disturbances Uses gain-scheduling techniques to tackle the probability-dependent control and filtering problems for time-varying nonlinear systems with incomplete information Evaluates the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with multiple random communication delays and random packet losses Examines the filtering problem for a class of nonlinear genetic regulatory networks with state-dependent stochastic disturbances and state delays Considers the H∞ state estimation problem for a class of discrete-time complex networks with probabilistic missing measurements and randomly occurring coupling delays Addresses the H∞ synchronization control problem for a class of dynamical networks with randomly varying nonlinearities Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities describes novel methodologies that can be applied extensively in lab simulations, field experiments, and real-world engineering practices. Thus, this text provides a valuable reference for researchers and professionals in the signal processing and control engineering communities.
Fitting Linear And Nonlinear Dynamic Models Using Different Kalman Filter Approaches
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Author : Sy-Miin Chow
language : en
Publisher:
Release Date : 2004
Fitting Linear And Nonlinear Dynamic Models Using Different Kalman Filter Approaches written by Sy-Miin Chow and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
Aircraft Surveillance And Collision Avoidance Using Gps
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Author : Ran Y. Gazit
language : en
Publisher:
Release Date : 1996
Aircraft Surveillance And Collision Avoidance Using Gps written by Ran Y. Gazit and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with categories.
International Aerospace Abstracts
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Author :
language : en
Publisher:
Release Date : 1990
International Aerospace Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Aeronautics categories.
Kalman Filtering
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Author : Mohinder S. Grewal
language : en
Publisher: John Wiley & Sons
Release Date : 2015-02-02
Kalman Filtering written by Mohinder S. Grewal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-02 with Technology & Engineering categories.
The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
Kalman Filtering
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Author : Charles K. Chui
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Kalman Filtering written by Charles K. Chui and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Science categories.
In addition to making a number of minor corrections and updat ing the references, we have expanded the section on "real-time system identification" in Chapter 10 of the first edition into two sections and combined it with Chapter 8. In its place, a very brief introduction to wavelet analysis is included in Chapter 10. Although the pyramid algorithms for wavelet decompositions and reconstructions are quite different from the Kalman filtering al gorithms, they can also be applied to time-domain filtering, and it is hoped that splines and wavelets can be incorporated with Kalman filtering in the near future. College Station and Houston Charles K. Chui September 1990 Guanrong Chen Preface to the First Edition Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more use ful even for very complicated real-time applications.
Factorization Methods For Discrete Sequential Estimation
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Author : Gerald J. Bierman
language : en
Publisher: Courier Corporation
Release Date : 2006-05-26
Factorization Methods For Discrete Sequential Estimation written by Gerald J. Bierman and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-26 with Mathematics categories.
This estimation reference text thoroughly describes matrix factorization methods successfully employed by numerical analysts, familiarizing readers with the techniques that lead to efficient, economical, reliable, and flexible estimation algorithms. Topics include a review of least squares data processing and the Kalman filter algorithm; positive definite matrices, the Cholesky decomposition, and some of their applications; Householder orthogonal transformations; sequential square root data processing; mapping effects and process noise; biases and correlated process noise; and covariance analysis of effects due to mismodeled variables and incorrect filter a priori statistics. The concluding chapters explore SRIF error analysis of effects due to mismodeled variables and incorrect filter a priori statistics as well as square root information smoothing. Geared toward advanced undergraduates and graduate students, this pragmatically oriented and detailed presentation is also a useful reference, featuring numerous helpful appendixes throughout the text.
Beyond The Kalman Filter Particle Filters For Tracking Applications
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Author : Branko Ristic
language : en
Publisher: Artech House
Release Date : 2003-12-01
Beyond The Kalman Filter Particle Filters For Tracking Applications written by Branko Ristic and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-01 with Technology & Engineering categories.
For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. Packed with 867 equations, this cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defense surveillance systems, and examines defense-related applications of particle filters to nonlinear and non-Gaussian problems. With this hands-on guide, you can develop more accurate and reliable nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of maneuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.