Robust Localization in Wireless Networks From Corrupted Signals

TL;DR

This paper introduces a robust, nonparametric localization method for wireless networks that effectively handles corrupted timing data without relying on specific noise distribution assumptions.

Contribution

A novel nonparametric approach that improves localization accuracy in wireless networks under corrupted data conditions, applicable across various timing-based techniques.

Findings

Demonstrates robustness in numerical experiments

Applicable to multiple timing-based localization methods

Requires only an upper bound on corrupted data fraction

Abstract

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.