Kalman filtering : theory and practice using MATLAB

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Kalman filtering : theory and practice using MATLAB / Mohinder S. Grewal, Angus P. Andrews

版:

2nd ed

資料種別:

図書

出版情報:

New York : Wiley, c2001

形態:

xiii, 401 p. ; 25 cm. + 1 disk

著者名:

ISBN:

9780471392545 [0471392545] (: cloth)

書誌ID:

BA52355308

子書誌情報

フルテキスト

所蔵情報

他の版・巻

Kalman filtering : theory and practice using MATLAB. 3rd ed (: hbk)
Mohinder S. Grewal, Angus P. Andrews , Wiley , 2008

書誌詳細

注記:

"A Wiley-Interscience publication"
"The first edition of this book was published by Prentice-Hall in 1993."--Pref
Includes bibliographical references (p. 381-393) and index

主題:

Kalman filtering; MATLAB

言語:

英語

目次情報:

Preface

Acknowledgments

General Information / 1：

On Kalman Filtering / 1.1：

On Estimation Methods / 1.2：

On the Notation Used in This Book / 1.3：

Summary / 1.4：

Problems

Linear Dynamic Systems / 2：

Chapter Focus / 2.1：

Dynamic Systems / 2.2：

Continuous Linear Systems and Their Solutions / 2.3：

Discrete Linear Systems and Their Solutions / 2.4：

Observability of Linear Dynamic System Models / 2.5：

Procedures for Computing Matrix Exponentials / 2.6：

Random Processes and Stochastic Systems / 2.7：

Probability and Random Variables / 3.1：

Statistical Properties of Random Variables / 3.3：

Statistical Properties of Random Processes / 3.4：

Linear System Models of Random Processes and Sequences / 3.5：

Shaping Filters and State Augmentation / 3.6：

Covariance Propagation Equations / 3.7：

Orthogonality Principle / 3.8：

Linear Optimal Filters and Predictors / 3.9：

Kalman Filter / 4.1：

Kalman--Bucy Filter / 4.3：

Optimal Linear Predictors / 4.4：

Correlated Noise Sources / 4.5：

Relationships between Kalman and Wiener Filters / 4.6：

Quadratic Loss Functions / 4.7：

Matrix Riccati Differential Equation / 4.8：

Matrix Riccati Equation in Discrete Time / 4.9：

Relationships between Continuous and Discrete Riccati Equations / 4.10：

Model Equations for Transformed State Variables / 4.11：

Application of Kalman Filters / 4.12：

Smoothers / 4.13：

Nonlinear Applications / 4.14：

Problem Statement / 5.1：

Linearization Methods / 5.3：

Linearization about a Nominal Trajectory / 5.4：

Linearization about the Estimated Trajectory / 5.5：

Discrete Linearized and Extended Filtering / 5.6：

Discrete Extended Kalman Filter / 5.7：

Continuous Linearized and Extended Filters / 5.8：

Biased Errors in Quadratic Measurements / 5.9：

Application of Nonlinear Filters / 5.10：

Implementation Methods / 5.11：

Computer Roundoff / 6.1：

Effects of Roundoff Errors on Kalman Filters / 6.3：

Factorization Methods for Kalman Filtering / 6.4：

Square-Root and UD Filters / 6.5：

Other Alternative Implementation Methods / 6.6：

Practical Considerations / 6.7：

Detecting and Correcting Anomalous Behavior / 7.1：

Prefiltering and Data Rejection Methods / 7.3：

Stability of Kalman Filters / 7.4：

Suboptimal and Reduced-Order Filters / 7.5：

Schmidt--Kalman Filtering / 7.6：

Memory, Throughput, and Wordlength Requirements / 7.7：

Ways to Reduce Computational Requirements / 7.8：

Error Budgets and Sensitivity Analysis / 7.9：

Optimizing Measurement Selection Policies / 7.10：

Application to Aided Inertial Navigation / 7.11：

MATLAB Software / 7.12：

Notice / A.1：

General System Requirements / A.2：

Diskette Directory Structure / A.3：

MATLAB Software for Chapter 2 / A.4：

MATLAB Software for Chapter 4 / A.5：

MATLAB Software for Chapter 5 / A.6：

MATLAB Software for Chapter 6 / A.7：

MATLAB Software for Chapter 7 / A.8：

Other Sources of Software / A.9：

A Matrix Refresher / Appendix B：

Matrix Forms / B.1：

Matrix Operations / B.2：

Block Matrix Formulas / B.3：

Functions of Square Matrices / B.4：

Norms / B.5：

Cholesky Decomposition / B.6：

Orthogonal Decompositions of Matrices / B.7：

Quadratic Forms / B.8：

Derivatives of Matrices / B.9：

References

Index

Preface

Acknowledgments

General Information / 1：

On Kalman Filtering / 1.1：

On Estimation Methods / 1.2：

On the Notation Used in This Book / 1.3：

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