Kalman filtering :
xvii, 617 p. : illustrations ; 24 cm. Content notes : 1. Introduction --
2. Linear dynamic systems --
3. Probability and expectancy --
4. Random processes --
5. Linear optimal filters and predictors --
6. Optimal smoothers --
7. Implementation methods --
8. Nonlinear approximations --
9. Practical considerations --
10. Applications to navigation --
Appendix A: software --
Index. MATLAB. Kalman-Filter.