Kalman filtering : theory and practice using MATLAB
著者
書誌事項
Kalman filtering : theory and practice using MATLAB
Wiley, 2008
3rd ed
- : hbk
大学図書館所蔵 全26件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
Previous ed.: published in 2001
内容説明・目次
内容説明
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.
目次
Preface ix Acknowledgments xiii List of Abbreviations xv 1 General Information 1 1.1 On Kalman Filtering, 1 1.2 On Optimal Estimation Methods, 5 1.3 On the Notation Used In This Book, 23 1.4 Summary, 25 Problems, 26 2 Linear Dynamic Systems 31 2.1 Chapter Focus, 31 2.2 Dynamic System Models, 36 2.3 Continuous Linear Systems and Their Solutions, 40 2.4 Discrete Linear Systems and Their Solutions, 53 2.5 Observability of Linear Dynamic System Models, 55 2.6 Summary, 61 Problems, 64 3 Random Processes and Stochastic Systems 67 3.1 Chapter Focus, 67 3.2 Probability and Random Variables (RVs), 70 3.3 Statistical Properties of RVs, 78 3.4 Statistical Properties of Random Processes (RPs), 80 3.5 Linear RP Models, 88 3.6 Shaping Filters and State Augmentation, 95 3.7 Mean and Covariance Propagation, 99 3.8 Relationships Between Model Parameters, 105 3.9 Orthogonality Principle, 114 3.10 Summary, 118 Problems, 121 4 Linear Optimal Filters and Predictors 131 4.1 Chapter Focus, 131 4.2 Kalman Filter, 133 4.3 Kalman-Bucy Filter, 144 4.4 Optimal Linear Predictors, 146 4.5 Correlated Noise Sources, 147 4.6 Relationships Between Kalman-Bucy and Wiener Filters, 148 4.7 Quadratic Loss Functions, 149 4.8 Matrix Riccati Differential Equation, 151 4.9 Matrix Riccati Equation In Discrete Time, 165 4.10 Model Equations for Transformed State Variables, 170 4.11 Application of Kalman Filters, 172 4.12 Summary, 177 Problems, 179 5 Optimal Smoothers 183 5.1 Chapter Focus, 183 5.2 Fixed-Interval Smoothing, 189 5.3 Fixed-Lag Smoothing, 200 5.4 Fixed-Point Smoothing, 213 5.5 Summary, 220 Problems, 221 6 Implementation Methods 225 6.1 Chapter Focus, 225 6.2 Computer Roundoff, 227 6.3 Effects of Roundoff Errors on Kalman Filters, 232 6.4 Factorization Methods for Square-Root Filtering, 238 6.5 Square-Root and UD Filters, 261 6.6 Other Implementation Methods, 275 6.7 Summary, 288 Problems, 289 7 Nonlinear Filtering 293 7.1 Chapter Focus, 293 7.2 Quasilinear Filtering, 296 7.3 Sampling Methods for Nonlinear Filtering, 330 7.4 Summary, 345 Problems, 350 8 Practical Considerations 355 8.1 Chapter Focus, 355 8.2 Detecting and Correcting Anomalous Behavior, 356 8.3 Prefiltering and Data Rejection Methods, 379 8.4 Stability of Kalman Filters, 382 8.5 Suboptimal and Reduced-Order Filters, 383 8.6 Schmidt-Kalman Filtering, 393 8.7 Memory, Throughput, and Wordlength Requirements, 403 8.8 Ways to Reduce Computational Requirements, 409 8.9 Error Budgets and Sensitivity Analysis, 414 8.10 Optimizing Measurement Selection Policies, 419 8.11 Innovations Analysis, 424 8.12 Summary, 425 Problems, 426 9 Applications to Navigation 427 9.1 Chapter Focus, 427 9.2 Host Vehicle Dynamics, 431 9.3 Inertial Navigation Systems (INS), 435 9.4 Global Navigation Satellite Systems (GNSS), 465 9.5 Kalman Filters for GNSS, 470 9.6 Loosely Coupled GNSS/INS Integration, 488 9.7 Tightly Coupled GNSS/INS Integration, 491 9.8 Summary, 507 Problems, 508 Appendix A MATLAB Software 511 A.1 Notice, 511 A.2 General System Requirements, 511 A.3 CD Directory Structure, 512 A.4 MATLAB Software for Chapter 2, 512 A.5 MATLAB Software for Chapter 3, 512 A.6 MATLAB Software for Chapter 4, 512 A.7 MATLAB Software for Chapter 5, 513 A.8 MATLAB Software for Chapter 6, 513 A.9 MATLAB Software for Chapter 7, 514 A.10 MATLAB Software for Chapter 8, 515 A.11 MATLAB Software for Chapter 9, 515 A.12 Other Sources of Software, 516 Appendix B A Matrix Refresher 519 B.1 Matrix Forms, 519 B.2 Matrix Operations, 523 B.3 Block Matrix Formulas, 527 B.4 Functions of Square Matrices, 531 B.5 Norms, 538 B.6 Cholesky Decomposition, 541 B.7 Orthogonal Decompositions of Matrices, 543 B.8 Quadratic Forms, 545 B.9 Derivatives of Matrices, 546 Bibliography 549 Index 565
「Nielsen BookData」 より