Robust Multihop Localization for Wireless Sensor Networks with Unreliable Beacons

Abstract

Multihop localization is a popular approach for determining the positions of normal nodes in large-scale wireless sensor networks. However, most existing multihop localization studies assume that the declared positions of beacon nodes are always reliable or even free of errors, which is not a valid assumption in practice. In this paper, we propose a robust multihop localization algorithm (RMLA) based on trust evaluation for diminishing the effect of unreliable beacons on the accuracy of node localization. Firstly, the trust evaluation framework is established on the basis of evidence theory. According to the multihop geometric relationship among nodes, every beacon evaluates the reliability of other beacons' declared positions. Then, the normal nodes integrate the evaluation results to obtain the total trust degrees of their multihop communication beacons, by use of an average method or an enhanced D-S evidence combination rule. Finally, the normal nodes employ the weighted Taylor-series least squares solver to estimate the optimal values of their coordinates. Extensive simulation results in isotropic and anisotropic networks show the robustness and effectiveness of our algorithm.