中文摘要：

节点定位是无线传感器网络（WSN）配置和运行的基本和关键问题之一。针对目前已有的多维标度（MDS）定位算法的局限性,提出了一种基于多维校正的分布式无线传感器网络多维标度定位算法（MDS-MC）。它通过自适应搜索算法建立局部节点定位区域（Nb）,保证了相邻Nb区域的坐标转换,减少了网络中的冗余公共节点;同时根据锚节点间的距离信息修正了节点间的距离估计,并将经典MDS算法与粒子群算法相结合,优化了节点的位置估计,解决了节点间距离不完整时的定位问题。在此基础上,研究了不同场景下节点的定位误差和能耗。实验结果表明,该算法定位精度高、能耗小,特别是对非理想环境有很好的鲁棒性,满足大规模无线传感器网络应用的需要。

英文摘要：

Sensor localization is one of the crucial issues for the configuration and operation of wireless sensor work （WSN）. Aiming at the limitations of existing MDS-based localization algorithms, a novel distributed localization algorithm （MDS-MC） for WSN was proposed based on multidimensional scaling and multidimensional calibration. In the MDS-MC, the local positioning （Nb） regions are established using an adaptive search algorithm, which not only ensures that the relative coordinates of the sensors can be transformed between neighbor Nb regions, but also reduces the number of redundant common sensors. In each Nb region, the estimated distances between sensors are corrected with the distances between anchors. Using particle swarm optimization and classical MDS algorithm, the relative positions of the sensors are computed and optimized even when the distance estimation matrix is incomplete. The performances of the MDS-MC were validated in different scenarios. Experimental results show that the proposed MDSMC is an energy-efficient algorithm with small localization error and has strong robustness to range errors in different sensor deployments, which can meet the requirements of large-scale WSN applications.