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Produktbild: Bayesian Estimation

Bayesian Estimation

163,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

04.06.2012

Abbildungen

Graphs: 100 B&W, 0 Color

Verlag

John Wiley & Sons

Seitenzahl

400

Maße (L/B/H)

24/16,1/2,6 cm

Gewicht

759 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-62170-7

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

04.06.2012

Abbildungen

Graphs: 100 B&W, 0 Color

Verlag

John Wiley & Sons

Seitenzahl

400

Maße (L/B/H)

24/16,1/2,6 cm

Gewicht

759 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-62170-7

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Bayesian Estimation
  • Preface
     
    Acknowledgments
     
    List of Figures xi

    List of Tables xxi
     
    Part I. Prelininaries
     
    1. Introduction 3
     
    1.1 Bayesian Inference 5
     
    1.2 Bayesian Hierarchy of Estimation Methods 7
     
    1.3 Scope of this Text 8
     
    1.4 Modeling and Simulation with Matlab(r) 13
     
    2. Preliminary Mathematical Concepts 19
     
    2.1 A Very Brief Overview of Matrix Linear Algebra 20
     
    2.2 Vector Point Generators 27
     
    2.3 Approximating Nonlinear Multidimensional Functions with Multidimensional Arguments 32
     
    2.4 Overview of Multivariate Statistics 47
     
    3. General Concepts of Bayesian Estimation 69
     
    3.1 Bayesian Estimation 70
     
    3.2 Point Estimators 72
     
    3.3 Introduction to Recursive Bayesian Filtering of Probability Density Functions 76
     
    3.4 Introduction to Recursive Bayesian Estimation of the State Mean and Covariance 81
     
    3.5 Discussion of General Estimation Methods 88
     
    4. Case Studies: Preliminary Discussions 93
     
    4.1 The Overall Simulation/Estimation/Evaluation Process 94
     
    4.2 A Scenario Simulator for Tracking a Constant-Velocity Target Through a DIFAR Buoy Field 97
     
    4.3 DIFAR Buoy Signal Processing 102
     
    4.4 The DIFAR Likelihood Function 111
     
    Part II. The Gaussian Assumption: A Family of Kalman Filter Estimators
     
    5. The Gaussian Noise Case: Multidimensional Integration of Gaussian-Weighted Distributions 119
     
    5.1 Summary of Important Results From Chapter 3 122
     
    5.2 Derivation of the Kalman Filter Correction (Update) Equations Revisted 124
     
    5.3 The General Bayesian Point Prediction Integrals for Gaussian Densities 128
     
    6. The Linear Class of Kalman Filters 141
     
    6.1 Linear Dynamic Models 142
     
    6.2 Linear Observation Models 143
     
    6.3 The Linear Kalman Filter 144
     
    6.4 Application of the LKF to DIFAR Buoy Bearing Estimation 146
     
    7. The Analytical Linearization Class of Kalman Filters: The Extended Kalman Filter 153
     
    7.1 One-Dimensional Consideration 154
     
    7.2 Multidimensional Consideration 159
     
    7.3 An Alternate Derivation of the Multidimensional Covariance Prediction Equations 172
     
    7.4 Application of the EKF to the DIFAR Ship Tracking Case Study 174
     
    8. The Sigma Point Class: The Finite Difference Kalman Filter 187
     
    8.1 One-Dimensional Finite Difference Kalman Filter 189
     
    8.2 Multidimensional Finite Difference Kalman Filters 195
     
    8.3 An Alternate Derivation of the Multidimensional Finite Difference Covariance Prediction Equations 201
     
    9. The Sigma Point Class: The Unscented Kalman Filter 207
     
    9.1 Introduction to Monomial Cubature Integration Rules 207
     
    9.2 The Unscented Kalman Filter 211
     
    9.3 Applications of the UKF to the DIFAR Ship Tracking Case Study 221
     
    10. The Sigma Point Class: The Spherical Simplex Kalman Filter 227
     
    10.1 One-Dimensional Spherical Simplex Sigma Points 228
     
    10.2 Two-Dimensional Spherical Simplex Sigma Points 229
     
    10.3 Higher-Dimensional Spherical Simplex Sigma Points 233
     
    10.4 The Spherical Simplex Kalman Filter 233
     
    10.5 The Spherical Simplex Kalman Filter Process 236
     
    10.6 Application of the SSKF to the DIFAR Ship Tracking Case Study 236
     
    11. The Sigma Point Class: The Gauss-Hermite Kalman Filter 241
     
    11.1 One-Dimensional Gauss-Hermite Quadrature 242
     
    11.2 One-Dimensional Gauss-Hermite Kalman Filter 248
     
    11.3 Multidimensional Gauss-Hermite Kalman Filter 251
     
    11.4 Sparse Grid Approximation for High Dimension/High Polynomial Order 257