History-based multi-node collaborative localization in mobile wireless ad hoc networks

Recent years have witnessed a growing interest in localization algorithms for wireless ad hoc networks. In most localization algorithms, increasing the density of anchor nodes is one of the main strategies to improve the localization accuracy in dense networks. In this paper, based on the number of reference nodes, we propose a distributed localization algorithm, i.e., history based multi-node collaborative localization algorithm (HMCL), which provides a potential approach for localization in sparse ad hoc wireless networks. In the proposed HMCL algorithm, we exploit a new motion model to filter the imprecise estimation values based on the historical position information of nodes, which can improve the localization accuracy and reduce the computation overhead and energy consumption. Moreover, we utilize different strategies to achieve the localization of nodes with different priorities measured by the distance information between neighbor nodes. We verify through experiment that the proposed algorithm provides better performance in terms of localization precision and energy consumption. Besides, we also analyze the effect of the number of neighbor nodes, node density and moving speed of nodes on localization precision.