A deep analysis of finite localization using iterative sweeps in sparse WSNs

Sweeps is a well-known localization algorithm based on the consistent connection constraints in WSN, and utilizes the concept of finite localization to relax the constraint conditions from trilateration to bilateration. In this paper, we deeply analyze the finite localization in various localization environments, and uniquely localize the finitely localized node without flip ambiguities using iterative Sweeps. The theoretical proof results show the correctness of our localization methods. A localization algorithm called Deep Sweeps Localization Algorithm is developed based on these methods. The simulation results validate the efficiency of this algorithm in terms of the percentage of localizable nodes.