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。 Wireless sensor networks are many intelligent beacon nodes through wireless multi-hop communication, mainly for the perception of the external environment, and the perception of information processing, so as to target the precise positioning and tracking. In the wireless sensor network node location algorithm, although the more nodes, the more accurate the positioning process, but the cost is too high. In addition, after the unknown node location is completed, the beacon node becomes an ordinary node. In order to solve the above problems, a Gauss-Markov model based wireless sensor localization method is proposed. The moving beacons automatically change speed according to the change of external environment. In different situations, different speed is adopted to obtain more virtual coordinate and improve efficiency. Finally, the algorithm is verified by simulation. The experimental results show that the algorithm can effectively reduce the operating cycle of the algorithm and greatly improve the positioning accuracy.