Joint localization and cooperative detection in location-aware wireless networks in the presence of ranging outliers

Location-aware wireless networks can provide precise location information in harsh environments only when all anchors are well-functioning. In this paper, we propose a distributed, robust TOA-based localization approach based on the Expectation-Maximization (EM) algorithm, which enables the agents to detect the malfunctioning anchors cooperatively while localizing themselves. Closed-form solution is obtained by using Taylor approximation. Moreover, performance limit is analyzed using Cramér-Rao lower bound (CRLB), which reveals that cooperative outlier detection brings theoretical localization performance gain. Simulation results show that the proposed method attains the performance limit with a significantly lower computational cost compared with the existing algorithms.