Robust localization in wireless networks from corrupted signals

We address the problem of timing-based localization in wireless networks, when an unknown fraction of data is corrupted by non-ideal propagation conditions. While timing-based techniques can enable accurate localization, they are sensitive to corrupted data. We develop a robust method that is applicable to a range of localization techniques, including time-of-arrival, time-difference-of-arrival and time-difference in schedule-based transmissions. The method is distribution-free, is computationally efficient and requires only an upper bound on the fraction of corrupted data, thus obviating distributional assumptions on the corrupting noise. The robustness of the method is demonstrated in numerical experiments.