A Suboptimal Approximation to the Kalman Filter PDF Download
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Author: Leon Bess
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 36
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Book Description
Author: Leon Bess
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 36
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Book Description
Author: Guanrong Chen
Publisher: World Scientific
ISBN: 9789810213596
Category : Computers
Languages : en
Pages : 248
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Book Description
Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear dynamic-observation system, under the regular conditions such as perfect data information; complete noise statistics; exact linear modeling; ideal well-conditioned matrices in computation and strictly centralized filtering.In practice, however, one or more of the aforementioned conditions may not be satisfied, so that the standard Kalman filtering algorithm cannot be directly used, and hence ?approximate Kalman filtering? becomes necessary. In the last decade, a great deal of attention has been focused on modifying and/or extending the standard Kalman filtering technique to handle such irregular cases. It has been realized that approximate Kalman filtering is even more important and useful in applications.This book is a collection of several tutorial and survey articles summarizing recent contributions to the field, along the line of approximate Kalman filtering with emphasis on both its theoretical and practical aspects.
Author: Farshad Rafii
Publisher:
ISBN:
Category : Kalman filtering
Languages : en
Pages : 268
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Book Description
Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
ISBN: 1118210468
Category : Technology & Engineering
Languages : en
Pages : 458
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Book Description
This book provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. It has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department -- to obtain the manual, send an email to
[email protected].
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 938
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Book Description
Author: The Analytic Sciences Corporation
Publisher: MIT Press
ISBN: 9780262570480
Category : Computers
Languages : en
Pages : 388
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Book Description
This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation. Even so, theoretical and mathematical concepts are introduced and developed sufficiently to make the book a self-contained source of instruction for readers without prior knowledge of the basic principles of the field. The work is the product of the technical staff of The Analytic Sciences Corporation (TASC), an organization whose success has resulted largely from its applications of optimal estimation techniques to a wide variety of real situations involving large-scale systems. Arthur Gelb writes in the Foreword that "It is our intent throughout to provide a simple and interesting picture of the central issues underlying modern estimation theory and practice. Heuristic, rather than theoretically elegant, arguments are used extensively, with emphasis on physical insights and key questions of practical importance." Numerous illustrative examples, many based on actual applications, have been interspersed throughout the text to lead the student to a concrete understanding of the theoretical material. The inclusion of problems with "built-in" answers at the end of each of the nine chapters further enhances the self-study potential of the text. After a brief historical prelude, the book introduces the mathematics underlying random process theory and state-space characterization of linear dynamic systems. The theory and practice of optimal estimation is them presented, including filtering, smoothing, and prediction. Both linear and non-linear systems, and continuous- and discrete-time cases, are covered in considerable detail. New results are described concerning the application of covariance analysis to non-linear systems and the connection between observers and optimal estimators. The final chapters treat such practical and often pivotal issues as suboptimal structure, and computer loading considerations. This book is an outgrowth of a course given by TASC at a number of US Government facilities. Virtually all of the members of the TASC technical staff have, at one time and in one way or another, contributed to the material contained in the work.
Author: Branko Ristic
Publisher: Artech House
ISBN: 9781580538510
Category : Technology & Engineering
Languages : en
Pages : 328
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Book Description
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.
Author: Víctor M. Moreno
Publisher: BoD – Books on Demand
ISBN: 9533070005
Category : Computers
Languages : en
Pages : 608
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Book Description
The aim of this book is to provide an overview of recent developments in Kalman filter theory and their applications in engineering and scientific fields. The book is divided into 24 chapters and organized in five blocks corresponding to recent advances in Kalman filtering theory, applications in medical and biological sciences, tracking and positioning systems, electrical engineering and, finally, industrial processes and communication networks.
Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
ISBN: 1118984919
Category : Technology & Engineering
Languages : en
Pages : 638
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Book Description
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.
Author: Clive D Rodgers
Publisher: World Scientific
ISBN: 9814498688
Category : Science
Languages : en
Pages : 256
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Book Description
Remote sounding of the atmosphere has proved to be a fruitful method of obtaining global information about the atmospheres of the earth and other planets. This book treats comprehensively the inverse problem of remote sounding, and discusses a wide range of retrieval methods for extracting atmospheric parameters of interest from the quantities (thermal emission, for example) that can be measured remotely. Inverse theory is treated in depth from an estimation-theory point of view, but practical questions are also emphasized, such as designing observing systems to obtain the maximum quantity of information, efficient numerical implementation of algorithms for processing large quantities of data, error analysis and approaches to the validation of the resulting retrievals. The book is targeted at graduate students as well as scientists.
