Tuning of the continuous-time Kalman filter from sampled data

This paper introduces a novel way to identify a stochastic continuous-time state space systems from sampled data. This allows us to tune a continuous-time Kalman filter. The key in solving this identification problem is the use a bank of Laguerre filters, which is used to transform the original system description to a so called w-domain.