无线传感器网络是有许多智能的信标节点通过无线多跳的通信方式组成,主要是对外部环境进行感知,并对感知信息进行处理,从而对目标进行精确定位和跟踪。在无线传感器网络节点定位算法中,虽然节点个数越多,定位过程中精度越高,但成本过高,此外未知节点定位完成后,信标节点从而成为普通的节点。针对以上问题提出了一种Gauss-Markov模型的无线传感器定位方法,使移动信标根据外部环境变化自动改变速度,在不同情况下采用不同的速度以获取更多的虚拟信坐标并提高效率。最后通过仿真对该算法进行验证,实验结果说明该算法能够有效缩减算法运行周期,大大提高定位精度。

There are many intelligent wireless sensor network communication over wireless multi-hop beacon nodes form, mainly is to perceive the external environment, and the processing of sensory information, so it is propitious to precise positioning and tracking the target. Node localization algorithm in wireless sensor networks, number of nodes is more precision in the positioning of the higher, but its costs are too high, and in addition unknown localization is complete, beacon nodes and thus become a common node. To solve the above problems,this paper presented Gauss-Markov model of wireless sensor positioning method, mobile beacon automatically change speed based on changes in the external environment, with different speed in different situations to get more virtual coordinate and improve efficiency. Finally to verify the algorithms through simulation, experiments show that this algorithm can effectively reduce the running cycle, greatly improve the positioning accuracy.