Estimation theory and Kalman filtering

Estimation theory and Kalman filtering: Estimation theory deals with parameter estimation for models of physical processes, or estimation and tracking of the internal "state" of a system/process given some noisy measurements of the outputs of the system. Kalman filters are one of the most effective and widely used estimation algorithms in engineering. The focus of our research is development of distributed Kalman filtering algorithms for observing and tracking multiple events in an environment using sensor networks.

Faculty contact: Reza Olfati-Saber