基于负载均衡分簇的无线传感器网络目标跟踪算法

Target tracking algorithm for wireless sensor networks based on load balancing clustering

针对无线传感器网络目标跟踪算法节点负载不均衡的现状,结合非线性模型下目标跟踪的研究,提出一种基于负载均衡分簇的无线传感器网络目标跟踪算法.采用分簇时选出高能量簇首,簇间通信时通过辅助簇首多跳通信,在跟踪目标时使用分布式扩展卡尔曼滤波的方法.仿真结果表明:本文算法在多次分簇后有效减少了死亡节点数量降低了节点剩余能量差,与分布式卡尔曼滤波相比降低了跟踪误差.该算法均衡了无线传感器网络节点的负载并提高了非线性模型下目标跟踪的精度,在有限的资源下增加了目标跟踪算法的可靠性.

Aiming at the status quo of node load imbalance in wireless sensor network target tracking algorithm and combined with the research on target tracking in nonlinear model, this paper proposed a wireless sensor network target tracking algorithm based on load balancing clustering. During the clustering process, the high energy cluster head was elected, and the auxiliary cluster head mechanism was adopted to reduce the cluster head load, and the extended Kalman filter was used to track the target. Simulation results show that the algorithm can effectively reduce the number of nodes in the cluster and reduce the residual energy difference, and the tracking error is reduced compared with the distributed Kalman filter. According to the simulation results, the algorithm can balance the load of wireless sensor network nodes and improve the accuracy of target tracking in nonlinear model.