Link state based annulus localization algorithm for wireless sensor networks

Most of the state-of-the-art localization systems assume an idealistic radio propagation model that is far from the reality, and will lead to lower localization accuracy in real wireless sensor networks. In this paper we describe a coarse-grained Link State Based Annulus (LSBA) localization algorithm that takes into account the anisotropic feature of real radio propagation to improve the localization accuracy and adapts to deployment irregularity as well. We compare LSBA with four typical coarse-grained localization algorithms: Centroid, APIT, DV-HOP and Amorphous in simulated realistic settings, and experimental results show that LSBA achieves the best tradeoff between localization accuracy and convergence speed in networks with moderate number of anchors. Based on our observation, we also make an improvement suggestion on DV-HOP and Amorphous to redefine the concept of neighboring nodes to reflect the radio irregularity, and simulation results show that both improved algorithms see increased localization accuracy.