FILTERING FOR STOCHASTIC PROCESSES WITH APPLICATIONS TO GUIDANCE

Contents:

Part I. Theory

1. Ordinary differential equations and stability

2. Random process and stochastic models

3. Observability and controllability

4. Filtering theory

5. Global theory of filtering

6. Stochastic stability

7. Optimal filtering for correlated noise process

8. Approximate optimal non-linear filtering

9. Optimum filtering for discrete time random process

10. Stochastic control

11. Open questions and historical comments

Part II. Applications

12. Application to navigation

13. Applications of filter theory and modeling techniques

14. Free flight and powered flight navigation

15. Error analyses and sub-optimal modeling

16. Errors in the filtering process

Appendix A. Least squares curve fitting

Appendix B. Probability review

Appendix C. The Riccati equation and its bounds

Appendix D. Further references