Abstract
Location-aware wireless networks can provide precise location information in harsh environments, however, which is only possible when all nodes are well-functioning. In this paper, we propose algorithms and analyze the performance limits for both non-cooperative and cooperative localization networks in the presence of ranging outliers. Especially, we show that the localization performance can be boosted by using the cooperative outlier detection scheme. An algorithm based on expectation-maximization is proposed for non-cooperative localization networks, while a variational message passing-based algorithm is proposed for the cooperative counterparts. Performance limits are investigated using Cramer–Rao lower bound. Further inspection on the performance limits confirms the performance gain from the cooperative detection scheme. Stochastic geometric analysis is also carried out to account for the stochastic nature of wireless networks, as well as to provide simpler expressions and additional insights. Simulation results corroborate the analytical results, and show that both of the proposed algorithms are capable of attaining the corresponding performance limits at a significantly reduced computational cost compared with existing algorithms.
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