The Multidimensional Scaling Positioning Algorithm for Wireless Sensor Networks Based on Distance Reconstruction

The multidimensional scaling( MDS) positioning algorithms of wireless sensor networks usually calculate the unknown items of the distance matrix by the shortest path,which may result in large positioning errors. To solve this problem,we propose the multidimensional scaling localization algorithm based on distance reconstruction( DRMDS). The algorithm uses the common neighbor information between nodes for distance matrix reconstruction,which can effectively calculate the unknown. Then,we calculate the coordinates by making full use of the spatial correlation between all nodes. Simulation results show that the proposed DR-MDS algorithm get higher positioning accuracy and lower error range compared to the MDS-MAP and ISOMAP.