Globally optimal distributed time-varying weight information filter of mobile sensor network

Abstract The networked state estimation for a linear dynamic system is studied in this paper. Firstly, a time-varying distributed communication protocol governed by the network topology is introduced for delivering information among the neighboring sensors. Secondly, based on this protocol, a two stage distributed state estimation algorithm is presented to achieve the global optimal results in a least square sense. In the first stage of the proposed algorithm, distributed computation on the sum of global information vector contributions is conducted, and the second stage is to derive the state estimations via utilizing the interaction results offered by the first stage. Thirdly, it is shown that the proposed algorithm only demands finite neighbor interaction times to obtain global optimal estimations. The optimality and stability properties of the proposed algorithm are also proved by using the Riccati equation. Finally, through numerical simulations, it is further illustrated that the proposed algorithm could outperform the previous distributed estimators.

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