Journal of East China Normal University(Natural Sc ›› 2019, Vol. 2019 ›› Issue (1): 115-123.doi: 10.3969/j.issn.1000-5641.2019.01.013

• Physics and Electronics • Previous Articles     Next Articles

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

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)

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