Robust Localization in Wireless Networks From Corrupted Signals
This addresses localization accuracy issues in wireless networks for applications like navigation or tracking, but it appears incremental as it builds on existing timing-based methods with a robustness enhancement.
The paper tackles the problem of timing-based localization in wireless networks when some data is corrupted by nonideal signal conditions, developing a robust nonparametric method that works with various localization techniques and requires only an upper bound on corruption fraction, with robustness demonstrated in numerical experiments.
We address the problem of timing-based localization in wireless networks, when an unknown fraction of data is corrupted by nonideal signal conditions. While timing-based techniques enable accurate localization, they are also sensitive to such 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 nonparametric and requires only an upper bound on the fraction of corrupted data, thus obviating distributional assumptions of the corrupting noise distribution. The robustness of the method is demonstrated in numerical experiments.