Improved Normalized Collinearity DV-Hop Algorithm for Node Localization in Wireless Sensor Network

Abstract

In recent years, collinearity theory is widely used in large-scale sensor network. When the anchor nodes are located at almost a straight line, the collinearity phenomenon will happen and usually cause negative influence on positioning accuracy. From detailed analysis of the relation between DV-Hop localization error and the collinearity, we proposed to select the anchor nodes which can meet the condition of hop count threshold and collinearity to participate in the localization procedure. Since there is uncertain situation that the anchor node's region is hard to be decided for the sensor nodes in one hop area, Voronoi diagram is adopted to divide the sensor network into several regions. Then, we can get the anchor node information in each Voronoi polygon. With this information and the collinearity condition, we can estimate the unknown node's position with relatively higher accuracy. Compared with the traditional DV-Hop and collinearity algorithm, our proposed algorithm can get better positioning accuracy in both homogeneous network and anisotropic network.