优化生存时间的无线传感器网数据融合

Data aggregation in wireless sensor network for optimizing network lifetime

以WSN中的目标跟踪为应用背景,研究基于扩展卡尔曼滤波法的优化生存时间数据融合问题,设计了一种兼顾跟踪准确度和节点能量的算法来实时地调度参与融合处理的节点组。仿真结果表明,当目标的移动速度在一定范围内时,提出的算法能使跟踪结果不偏移目标的运动轨迹。另外,与Random方法和All方法相比,提出的算法大大延长了WSN的生存时间。

Taking target tracking in wireless sensor network （WSN） as application background, data aggregation foroptimizing network lifetime based on extended Kalman filter method was researched, and an algorithm whichconsidered both tracking accuracy and node energy to real-time schedule node groups involved in the dataintegration was designed. Simulations show that the proposed algorithm makes the tracking results do not deviatefrom the trajectory of target as long as the target speed is within a certain speed range. In addition, compared withthe Random method and the All method, the proposed algorithm greatly prolongs network lifetime.