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General nonlinear continuous-time systems are considered for which its stateis estimated via a packet-based communication network. We assume that thesystem has multiple sensor nodes, affected by measurement noise, which cantransmit at discrete (non-equidistant) points in time. Moreover, each node cantransmit asynchronously. For this setup, we develop a state estimationframework, where the transmission instances of the individual sensor nodes canbe generated in either time-triggered or event-triggered fashions. In thelatter case, we guarantee the absence of Zeno behavior by construction. It isshown that, under the provided design conditions, an input-to-state stabilityproperty is obtained for the estimation error with respect to the measurementnoise and process disturbances and that the state is thus reconstructedasymptotically in the absence of noise. A numerical case study shows thestrengths of the developed framework.

Event-Triggered State Estimation with Multiple Noisy Sensor Nodes