Abstract: Due to the constraint that wireless sensor networks are composed of many wireless nodes with limited power, a new energy efficient distributed clustering Kalman consensus filtering algorithm is proposed. The convergence analysis for the algorithm is given by applying graph theory and matrix theory, and the conclusions show that the clustering process can accelerate the convergence rate of the system, reduce information transmission, and efficiently shorten communication distances among nodes. Moreover, the Gossip algorithm is introduced to deal with the consensus problem between cluster-heads for improving power consumption. Finally, a simulation example is presented to show that the proposed algorithm not only has better estimation performance but also decreases node energy consumption effectively, which greatly prolongs the life of the wireless sensor networks.