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文中在MCB(Monte-Carlo Localization Boxed)定位算法的基础上提出了一种新的移动无线传感器网络(Mobile Wireless Sensor Networks)节点的定位算法——权重MCB算法。MCB算法在定位过程中,在采样和滤波阶段用到了一阶锚节点和二阶锚节点的位置信息,而没有应用到邻居节点的位置信息。权重MCB在定位过程中不仅用到了一阶锚节点和二阶锚节点的位置信息,还应用到了一阶邻居节点的采样集合里的采样点(即一阶邻居节点的估计位置),从而改进了定位精度。对比MCB算法,权重MCB算法对定位精度的改进为13%～18%。
Based on the Monte Carlo Localization Boxed (MCB) localization algorithm, a new location algorithm of Mobile Wireless Sensor Networks (MCS) is proposed. The MCB algorithm uses the location information of the first-order anchor nodes and the second-order anchor nodes in the sampling and filtering phases in the positioning process without the location information applied to the neighboring nodes. The weighting MCB uses not only the location information of the first-order anchor nodes and the second-order anchor nodes but also the sampling points (ie, the estimated locations of the first-order neighboring nodes) in the sampling set of the first-order neighbor nodes so as to improve positioning accuracy. Compared with the MCB algorithm, the weight MCB algorithm improves the positioning accuracy by 13% ~ 18%.