Filtres de Kalman

Abstract

Kalman Filters are optimal estimation algorithms that have numerous applications in science and technology. They are one of the main topics in Control Theory and Control Systems, and they are shown to be very useful when tracking dynamic systems. In this thesis we present the Least-Squares Method as a previous step to Kalman Filters, for which we discuss some of their versions, like the Linear Kalman Filter, the Extendend Kalman Filter and nonlinear estimators. Then, some simple dynamical simulations are described in order to understand the implementation of a Kalman Filter. Finally, we conclude this work by introducing the basis of the problem of satellite Orbit Determination, one of the applications of Kalman Filering.