ENGR 621 Kalman Filtering

This course covers basic problem of state estimation (prediction, Kalman filtering, smoothing), the steady-state Kalman filtering for linearized state variable model, and state estimation for the "not-so-basic" state estimation. The state estimation is also discussed for nonlinear model. The course is accompanied with computer projects. Prerequisites: Random Signal Theory, EE 561 or equivalent.

Credits

3