Optimality and stability of event triggered consensus state estimation for wireless sensor networks

This paper presents distributed state estimation methods through wireless sensor networks with event triggered communication protocols among the sensors. Optimal consensus filters are derived which apply to generic non-uniform and asynchronous information exchange scenarios among neighboring sensors. To obtain a scalable covariance propagation algorithm, the optimal filter is approximated by a suboptimal filter. Homogeneous detection criteria are designed on each sensor node to determine the broadcasting instants. Thus, a consensus on state estimates is reached with all estimator sensors for the suboptimal consensus filter. The purpose of event detection is to achieve energy efficient operation by reducing unnecessary interactions among the neighboring sensors. In addition, the performance of the proposed state estimation algorithm is validated using a simulation example.