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针对无线传感器网络中节点能量有限的特点,利用分簇模型提出了一种新的能量高效的分布式卡尔曼一致性滤波算法.并结合图论、矩阵论对该算法进行了收敛分析,得出了分簇处理能加快系统的收敛速度,且能有效地减少节点间信息的传输量、缩短节点间的通信距离的结论.为进一步降低能量消耗,引入Gossip算法用于处理簇头级网络信息的一致性问题.仿真分析表明,所提出的算法不仅具有优越的估计性能,而且能有效地减少节点能量消耗,延长无线传感器网络的寿命.
Aiming at the limited energy of nodes in wireless sensor networks, a new energy-efficient distributed Kalman filtering algorithm based on clustering model is proposed. The convergence analysis of the algorithm based on graph theory and matrix theory shows that The clustering processing can speed up the convergence of the system and effectively reduce the transmission of information between nodes and shorten the communication distance between nodes.In order to further reduce the energy consumption, Gossip algorithm is introduced to deal with the cluster head network information The simulation results show that the proposed algorithm not only has superior estimation performance, but also can effectively reduce node energy consumption and extend the life of wireless sensor networks.