Abstract
The state estimation problem for discrete time-invariant systems with non-linear measurements over sensor networks under communication constraint is investigated in this paper. Communication in networks with constraint is that only one shared communication channel is available for message transmission at each time index, and therefore only partial measurements of sensors can be updated to the estimator. It is considered in this paper that the transmission nodes is given permissions for the communication channel on the basis of Round Robin protocol. A compensation strategy with weighted value and extended state-based form is adopted to solve the communication constraint, which transforms the system to be a linear time-variant one. Then an optimal linear filter is given based on the extended Kalman filter. Finally, simulation results are given to show the proposed filter is better than the hold on strategy by means of root mean square error.
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