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
Get Book Here
Book Description
Author: Leon Bess
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
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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: Guanrong Chen
Publisher:
ISBN:
Category : Approximation theory
Languages : en
Pages : 6
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Book Description
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.
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: 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:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 938
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Book Description
Author: Mohinder S. Grewal
Publisher: Wiley-Interscience
ISBN:
Category : Computers
Languages : en
Pages : 424
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Book Description
Disk contains: Demonstation programs and source code in MATLAB for algorithms in text.
Author: Clive D. Rodgers
Publisher: World Scientific
ISBN: 981022740X
Category : Science
Languages : en
Pages : 256
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Book Description
Annotation Rodgers (U. of Oxford) provides graduate students and other researchers a background to the inverse problem and its solution, with applications relating to atmospheric measurements. He introduces the stages in the reverse order than the usual approach in order to develop the learner's intuition about the nature of the inverse problem. Annotation copyrighted by Book News, Inc., Portland, OR.
Author: Robert Allen Crotteau
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
The object of this study is to find an approximation to the discrete optimal Kalman filter gain schedule by closed-form analytic expressions. In doing so, required table storage and/or on-line computation time can be reduced at little expense in terms of filter performance degradation. The method of least squares was used to determine the closed-form solution which was the best fit to the discrete Kalman filter gain schedule. The criterion for performance degradation was the difference between the values of the diagonal elements of the estimation covariance matrix, obtained by using the Kalman gain schedule, and the corresponding values obtained by using the closed-form analytic expressions for the elements of the gain matrix. Examples are presented to show that near-optimal results were obtained using this method. A comparison of the results of this study with another near-optimal estimation scheme is also included. (Author).
