Abstract
Considering the shortages of the classic MDS- MAP algorithm on localization precision and algorithm complexity, a distributional localization algorithm based on MDS had been proposed in this paper. The method of cluster was involved to build different clusters. MDS algorithm was used in every cluster for local relative coordinates, Euclidean algorithm was used to calculate the distance matrix in this step. Then the local maps were combined to form a global relative coordinate map based on matrix translation. Finally the relative coordinates was transferred to absolute coordinates by few beacon nodes. Simulation results demonstrated that the new algorithm can promote localization precision and perform well on low anisotropic topology.
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