George Mason University
George Mason University Mason
George Mason University

ECE 722: Kalman Filtering with Applications

Course Information from University Catalog

Not Repeatable


Detailed treatment of Kalman Filtering Theory and its applications, including some aspects of stochastic control theory. Topics include state-space models with random inputs, optimum state estimation, filtering, prediction and smoothing of random signals with noisy measurements, all within the framework of Kalman filtering. Additional topics are nonlinear filtering problems, computational methods, and various applications such as global positioning system, tracking, system control, and others. Stochastic control problems include linear-quadratic-Gaussian problem and minimum-variance control.

Hours of Lecture or Seminar per week: 3

Credits: 3

Prerequisites:

ECE 521 and 528 or equivalent, or permission of instructor.

1 Course Sections Scheduled for Spring 2018

Expertise