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In this paper, the information-weighted consensus filter (ICF) with partialinformation exchange is proposed to reduce the bandwidth of the signalstransmitted between the sensor nodes and guarantee its convergence to thecentralized Kalman filter (CKF). In the proposed algorithm, a part ofinformation chosen with the entry selection matrix is transmitted to the sensornodes in the neighborhood at each consensus step, and consensus averaging isconducted at each sensor node with the partial and the local information. Thisensures that the proposed distributed estimation algorithm converges to thecentralized algorithm, while allowing the proposed algorithm to achievebandwidth reduction of the signals transmitted between the sensors. With theproposed algorithm, the stability of the estimation error dynamics is provenand the convergence to the centralized algorithm is mathematically shown usingthe property of the average consensus. Simulations are conducted to validatethe proposed ICF with partial information exchange and the related theoreticalfindings.

Information-Weighted Consensus Filter with Partial Information Exchange