Improved DV-Hop Localization Algorithm Based on Weighted Least Squares Cycle Optimization in Anisotropic Networks

Node Localization has very broad application prospects in the field of wireless sensor networks and the Internet of Things. Among these localization algorithms, Distance Vector-Hop (DV-Hop) has drawn widespread interest because it provides a simple, feasible and low-cost localization scheme for isotropic networks. However, in anisotropic networks with obstacles and network holes, the localization accuracy of DV-Hop drops sharply due to the fact that the relationship between node distance and hops is not always linear. In order to solve the distance hops error, it is usually necessary to use a weighting function to correct the distance relationship between the hops, and at the same time select a better anchor node to improve the positioning accuracy. In this paper, we propose a weighted least squares cycle optimization DV-hop localization algorithm, which reduces the localization error of nodes by fusing the ideas of optimal weight function and reference anchor selection. Simulation results show that this algorithm has higher localization accuracy without requiring too much communication overhead.