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Self-Localization Algorithm for Deep Mine Wireless Sensor Networks Based on MDS and Rigid Subset

机译:基于MDS和刚性子集的深矿无线传感器网络自定位算法

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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.
机译:为了适应深矿道路的狭窄空间和复杂分支,对节点定位的准确性,基于MDS-MDS和刚性子集的深度矿无线传感器网络的自定位算法产生不利影响,(刚性 - 提出了MDS)。新的分布式算法基于刚性图论将整个网络划分为一些全局刚性子集,其中节点具有近距离空间相关,较少的跳跃和相似的路径方向与同一子集中的所有其他节点,并且它通过最短路径减少了误差。之后,选择靠近其他子集的边界节点作为锚点节点的框架,以定位整个网络。最后,使用均匀坐标系来进行几何变化。仿真结果表明,与MDS-MAP相比,刚性-MDS可以减少巷道分支中的误差。

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