Introduces theory and methods of statistical estimation for general linear and nonlinear dynamical systems, with emphasis on aerospace engineering applications. Major topics include: review of applied probability and statistics; optimal parameter and dynamic state estimation; theory and design of Kalman filters for linear systems; extended/unscented Kalman filters and general Bayesian filters for non-linear systems.
instructor(s)
Ahmed, Nisar Razzi
Primary Instructor
- Fall 2018 / Fall 2020 / Fall 2022 / Fall 2024
