Abstract: To reduce the energy consumption and extend the network’s survival time is the key research problem in the Wireless Sensor Network（WSN）.Much research work has been done on the placement of nodes and routing protocal，reducing data redundancy by density controlling and hierarchical clustering algorithm.In this paper，it is proposed that multi-sensor information fusion is an effective way to reduce the communication data and save the energy consumption.Three distributed sensor fusion methods are researched：fusion with weighted coefficients，Kalman fusion filtering without feedback and Kalman fusion filtering with feedback.The three algorithm are implemented in a temperature-measurement WSN.And then the three fusion methods are compared and analysed.Finally，the effectivity and conditionality of the fusion methods are summarized.

摘要： 节省能耗和延长网络寿命是无线传感器网络研究的核心课题之一，国内外在节点放置、路由策略方面有大量研究，通过密度控制、分级簇等路由算法减少数据冗余。通过信息融合算法减少有效数据传输量是延长网络节点寿命的有效途径，并就此进行具体研究，提出了三种典型的分布式信息融合算法，即系数加权融合、无反馈的Kalman融合滤波及有反馈的Kalman融合滤波，并对其在805.12.4/ZigBee温度测量网络应用层协议中进行实现，最后通过运算数据结果对三种算法进行了比较分析及有效性、局限性总结。