Abstract
AbstractIn this paper, we consider state estimation over a network subject to limited sensor communications. A sensor needs to decide when to send its local state estimate to a remote estimator in order to minimize the average estimation error at the estimator subject to that the total communication time is no more than a pre-specified value. We propose a novel sensor schedule that combines conventional time and event-based methods and demonstrate that the estimator performance is improved compared with the optimal time-based schedule and the computation complexity is reduced compared with the optimal event-based schedule. Thus the proposed schedule provides a tradeoff between the two classic approaches.
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