A measurement policy in stochastic linear filtering problems

With reference to a (discrete time) linear system filtering problem, we consider the problem of online deciding at which instant we actually measure and process the output values. We propose a convenient measurement policy, able to sensibly reduce the measurement cost, while keeping the estimate accuracy at satisfactory levels. By some probabilistic arguments we analyse the upper bounds for the measurement and nonmeasurement time intervals.