Description
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
