华东师范大学学报(自然科学版) ›› 2019, Vol. 2019 ›› Issue (1): 115-123.doi: 10.3969/j.issn.1000-5641.2019.01.013

• 物理学与电子学 • 上一篇    下一篇

基于核矩阵等距映射的无线传感网络节点定位算法

杨海1, 李兵1,2   

  1. 1. 湖南机电职业技术学院, 长沙 410151;
    2. 合肥工业大学 电气与自动化工程学院, 合肥 230009
  • 收稿日期:2017-09-19 出版日期:2019-01-25 发布日期:2019-01-24
  • 通讯作者: 李兵,男,副教授,研究生导师,研究方向为物联网技术.E-mail:libinghnu@163.com E-mail:libinghnu@163.com
  • 作者简介:杨海,男,副教授,研究方向为无线传感网络.E-mail:yanghai@foxmail.com.
  • 基金资助:
    国家自然科学基金（51777050）；湖南省自然科学基金（2017JJ2080）；湖南省教育厅科学研究项目（13C260）；安徽省自然科学基金（1508085MF112）；中央高校基本科研业务费（JDK16TD017）

Node localization of wireless sensor networks based on the kernel matrix ISOMAP algorithm

YANG Hai1, LI Bing1,2   

  1. 1. College of Hunan Mechanical and Electrical Polytechnic, Changsha 410151, China;
    2. School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China
  • Received:2017-09-19 Online:2019-01-25 Published:2019-01-24

RichHTML

10

PDF

349

摘要： 针对无线传感网络（Wireless Sensor Network，WSN）中节点位置信息呈现非线性的问题，基于偏最小二乘法（Partial Least Squares，PLS）稳健的多元线性回归特点，结合流形学习中的非线性降维方法，提出了一种基于PLS的核矩阵等距映射（Isometric Feature Mapping，ISOMAP）节点定位算法.通过节点间测地距离表征节点非相似性，利用样本点贡献率找寻和剔除邻域中的"短路"边，经质心变换和核变换后映射至高维特征区间，采用PLS方法求得节点位置.仿真结果表明，相比ISOMAP和多维尺度（Multidimensional Scale Method，MDS）算法，该算法具有良好的拓扑稳定性、泛化能力、稳健性和定位精度，降低了计算复杂度.

关键词: 无线传感网络, 节点定位, 核矩阵, 等距映射

Abstract: Position information is nonlinear in the node localization of wireless sensor networks (WSN). Based on the robust ability of multivariate linear regression of partial least squares (PLS), and in combination with nonlinear data dimension reduction of manifold learning, a novel kernel matrix ISOMAP (Isometric Feature Mapping) algorithm is proposed. Geodesic distances between nodes are used as a measure of dissimilarity, and the contribution rate is then used to find and delete the "short circuit" edge. The matrix constructed by a double-centered transformation and the kernel transformation trick is mapped to a high dimensional feature space; finally, the relative position is obtained by PLS. Compared with the traditional ISOMAP algorithm and the multidimensional scale method (MDS), simulation results indicate that the proposed algorithm has good topology stability, generalization properties, robustness, positioning accuracy, and lower computational complexity.

Key words: wireless sensor network, node localization, kernel matrix, Isometric Feature Mapping (ISOMAP)

中图分类号: