一种自适应煤矿井下环境的加权质心节点定位算法

A Weighted Centroid Node Localization Algorithm Self-adapting Environment in Coal-minel

摘要:

为提高煤矿井下无线传感器网络节点定位精度,提出了一种自适应煤矿井下工况环境的加权质心节点定位算法;在信标节点双链式部署结构的基础上,首先利用未知节点周围RSSI信号强度最大的信标节点之间的位置信息和信标节点的平均RSSI值自适应地估计环境参数,再应用无线信号强度衰减模型计算未知节点到信标节点的距离,最后采用加权质心定位算法的平均值确定最终的节点位置坐标;仿真实验结果表明,所提出方法的平均定位误差为0.94 m,有效降低了环境因素及RSSI的随机性对定位精度的影响,可用于煤矿井下无线传感器网络节点实时定位系统中。

Abstract:

In order to improve the location accuracy of wireless sensor networks nodes,a weighted centroid node localization algorithm self-adapting the environment in coal-mine is proposed. According to the double-chain deployment structure of beacon nodes, the location information among beacon nodes around,whose RSSI are the biggest, and the mean values of RSSI between beacon nodes are used to estimates self-adaptively the environmental parameters firstly. Then, the distances between unknown nodes and beacon nodes are calculated by signal strength model. Lastly, the mean value of of the multiple weighted centroid localization algorithm is taken as the location coordinates of unknown nodes. The simulation results show that the algorithm proposed can be self-adaptive to the environment and can effectively eliminate the random effect of RSSI on positioning performance. The mean localization error is 0.94 m and the algorithm can be applied to real-time positioning system in coal-mine. 