摘要： 在无线传感器网络节点移动定位过程中,网络拓扑结构不断进行更新,以致影响预测模型的精确度。为此,提出一种基于拉普拉斯映射的移动定位算法。分析无线传感器网络的布局特点,引入局部拓扑结构和非信标节点信息,将节点定位问题放在半监督框架中进行研究。实验结果表明,与同类算法相比,该算法提高了预测模型的泛化能力和节点的定位精度,具有更高的稳定性。

关键词: 无线传感器网络, 定位算法, 拉普拉斯映射, 半监督, 流形学习, 拓扑结构

Abstract: In the process of Wireless Sensor Network(WSN) node mobile localization,the network topology structure is updated constantly,which affects the accuracy of the predicted model.This paper proposes a mobile localization algorithm based on Laplacian mapping,analyzes the layout characteristics of WSN,introduces local topology information and non-beacon node information,and studies the node localization problem in the semi-supervision framework.Simulation results show that compared with similar algorithms,this algorithm improves the generalization ability of predicted model,increases the localization accuracy of nodes,and has higher stability.

Key words: Wireless Sensor Network(WSN), localization algorithm, Laplacian mapping, semi-supervision, manifold-based learning, topology structure

中图分类号: 

• TP393