Estimation Theory

4 credits

Development of computational tools for estimation and filtering of state variables from sensor measurements. Methods are presented for both linear and nonlinear systems. Topics include discrete and continuous system structures for both linear and nonlinear dynamical systems with notice; rigid body dynamics; least squares; Bayesian estimation; Kalman filtering; extended Kalman filtering; unscented Kalman filtering; particle filtering; smoothing. Course overlaps with: E E 549/A A 549/M E 549. Prerequisite: A E 510 Offered: A, even years.