Distributed range-free localization via hierarchical nonconvex constrained optimization

Localizing target nodes is a fundamental problem for wireless sensor networks (WSNs). Without range measurements, the range-free techniques, which only exploit the connectivity information among nodes, have been widely studied in the past score years. How to achieve a good balance between the localization accuracy and the communication cost has not been well solved. In this paper, we first decide the estimative region of a target node using the information from both its one-hop and two-hop neighboring anchors. Then we establish a Chebyshev center model to localize a single target inside its estimative region via a nonconvex optimization problem, which is solved by the proposed ADMM-based parallel efficient projection algorithm (PEPA). By introducing a hierarchical scheme, the PEPA is further applied to localize multiple targets layer by layer, which enjoys very low communication cost. Moreover, a novel heuristic layer-wise error correction mechanism is proposed to enhance the positioning precision. Simulation results illustrate the advantage of the proposed algorithms against the existing major range-free methods. (C) 2019 Elsevier B.V. All rights reserved.