基于MDS和刚性子集的深矿无线传感器网络自定位算法

Xiu-wu Yu, Lixing Zhou, Feng Zhang
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引用次数: 3

摘要

为适应深部矿井巷道空间狭窄、分支复杂对节点定位精度的不利影响,提出了一种基于MDS-MDS和刚性子集(rigid - mds)的深部矿井无线传感器网络自定位算法。新的分布式算法基于刚性图论,将整个网络划分为全局刚性子集,其中节点与同一子集中的所有节点具有密切的空间相关性、较少的跳数和相同的路径方向,并通过最短路径来减小误差。然后,选择与其他子集相近的边界节点作为框架,带锚节点对整个网络进行定位。最后,采用齐次坐标系进行几何变换。仿真结果表明,与MDS-MAP相比,刚性mds可以减小巷道支路误差。
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Self-localization algorithm for deep mine Wireless Sensor Networks based on MDS and rigid subset
In order to adapt to the narrow space and complex branch in deep mine roadway, which have an adverse impact on the accuracy of nodes localization, a self-localization algorithm for deep mine wireless sensor networks based on MDS-MDS and rigid subset (Rigid-MDS) was proposed. The new distributed algorithm divides whole network into some globally rigid subset based on rigid graph theory, in which nodes have close spatial correlation, less hop and alike path direction with all of other nodes in the same subset, and it reduces the error by shortest path. And afterwards, some boundary nodes close to other subsets is chosen as framework with anchor nodes to locate the whole network. Finally, homogeneous coordinate system is used to make the geometric change. Simulation results show that the Rigid-MDS can reduce error in the roadway branch compared with MDS-MAP.
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