Optimal Scheduling for State Estimation Using a Terminal Cost Function

Abstract

In this paper we consider state estimation problems where there are multiple independent processes evolving but the estimation scheme can only select a limited set of processes to measure at each time step. Within a Gauss-Markov framework, we show the optimality of a scheduling scheme under various scenarios. These types of problems are common in sensor scheduling applications