State estimation in a centralized sensor network under limited communication rate

This paper deals with the problem of estimating the state of a discrete-time linear stochastic dynamical system on the basis of data collected from multiple sensors subject to a limitation on the communication rate from the remote sensor units. More specifically, the attention is devoted to a centralized sensor network consisting of: (1) S remote nodes which collect measurements of the given system, compute state estimates at the full measurement rate and transmit them at a reduced communication rate; (2) a fusion node F that, based on received estimates, provides an estimate of the system state at the full rate. A measurement-independent strategy for deciding when transmitting estimates from each sensor to F will be considered. Sufficient conditions for the boundedness of the state covariance at node F will be given. Further, the possibility of determining a communication strategy with optimal performance in terms of minimum mean square estimation error will be investigated.