  The measure timetable plays a critical role for the accuracy of the
estimator. This article deals with the optimization of the schedule of measures
for observing a random process in time using a Kalman filter, when the length
of the process is finite and fixed, and a fixed number of measures are
available. The measuring devices are allowed to differ. The mean variance of
the estimator is chosen as criterion for optimality. The cases of $1$ or $2$
measures are studied in detail, and analytical formulas are provided.
