移动无线传感器网络下的采煤机定位精度

Positioning accuracy of shearer in mobile wireless sensor networks

基于节点的信号强度和距离解算模型,建立局域强信号与定位子空间的对偶映射,在此基础上推导包含测距误差和锚节点误差的拓展克拉美-罗下限方程。仿真研究无线测距误差、锚节点密度和锚节点基准坐标漂移方向等多因素对采煤机定位精度的影响,并在实验室三机模型上进行测试。实验结果表明:由无线测距误差引起的采煤机定位误差占到92.9%,且沿采煤机截割方向误差分量占78.11%以上,而通过增加锚节点密度以及减少移动节点与锚节点间垂直距离能减少定位误差。实验结果与仿真结果基本一致。研究结果可为移动传感器网络下采煤机精确定位提供理论与技术支撑。

Duality mapping between local strong signal set and positioning spatial domain were established by analyzing received signal strength and distance solver model. The improved Cramer-Rao lower bound formula was derived. The effects of wireless range error, anchor nodes density and the error drift direction of anchor node reference coordinate on positioning accuracy were simulated. Shearer positioning precision under mining fleet model was preceded in laboratory. Experiment results indicate that 92.9% of positioning error is caused by low ranging accuracy, while the positioning error along the shearer cutting direction accounts for 78.11%. Furthermore, increasing the anchor node density and decreasing the vertical distance between mobile node and anchor nodes can improve positioning accuracy. The practical monitoring results are similar to the simulation ones. So, shearer positioning using wireless sensor networks can be applied for mechanized mining faces under mobile wireless sensor networks.