ECE 722: Kalman Filtering with Applications
Course Information from University Catalog
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
1 Course Sections Scheduled for Spring 2018
ECE 722 - 001: |
W; 4:30 pm - 7:10 pm