Table of Contents
Preface
Acknowledgements
Authors
Introduction
Section I Mathematical Models, Kalman Filtering and H-Infinity Filters
1. Dynamic System Models and Basic Concepts
2. Filtering and Smoothing
3. H∞ Filtering
4. Adaptive Filtering
Section II Factorization and Approximation Filters
5. Factorization Filtering
6. Approximation Filters for Nonlinear Systems
7. Generalized Model Error Estimators for Nonlinear Systems
Section III Nonlinear Filtering, Estimation and Implementation Approaches
8. Nonlinear Estimation and Filtering
9. Nonlinear Filtering Based on Characteristic Functions
10. Implementation Aspects of Nonlinear Filters
11. Nonlinear Parameter Estimation
12. Nonlinear Observers
Section IV Appendixes – Basic Concepts and Supporting Material
Appendix A: System Theoretic Concepts – Controllability, Observability, Identifiability and Estimability
Appendix B: Probability, Stochastic Processes and Stochastic Calculus
Appendix C: Bayesian Filtering
Appendix D: Girsanov Theorem
Appendix E: Concepts from Signal and Stochastic Analyses
Appendix F: Notes on Simulation and Some Algorithms
Appendix G: Additional Examples
Index