Exploiting perturbed and coalescent anchor node geometry with semidefinite relaxation for sensor network localization

Abstract

Localization in wireless sensor networks (WSNs) suffer from performance issues whenever the anchor nodes (which are aware of their location) are subjected to motion from their usual position. Moreover, accurate localization demands more anchor nodes which is a scarce resource and needs to be used judiciously. In the current work, we propose a novel framework that addresses these two prime concerns by harnessing the inter relationship of anchor node geometry. For an unknown source node surrounded by anchor nodes, the anchors lying on the inner boundary of the deployment geometry may be carrying closely related information about source node, leading to redundancy and inefficient utilization. By anticipating the level of correlation between these anchors, localization can be made more frugal. Rigorous mathematical analysis is carried out to derive lower bounds on estimated locations. Based on fisher information from two proposed models, a convex estimation objective function is formulated using semidefinite programming (SDP) approach to validate the theoretical proceedings. Based on the findings, the proposed method is able to successfully extract useful information about the unknown source node location with limited number of anchor nodes, hence achieving superior localization.