Device-Level and System-Level Autocalibration of Ultra-Wide-Band Localization

We show how accuracy of Ultra-Wide-Band (UWB) localization is improved by removing systematic errors (bias) on both device-level and system-level. On device-level, we discern the different sources of bias and establish a method that determines their values, for specific hardware and for individual devices. To this end, a dedicated test setup was built. On system-level, we developed a method that avoids measuring all anchor positions one by one by exploiting increased redundancy from anchor-to-anchor and anchor-to-tag ranges, and automatically calculating the anchors topology (relative positions between each other). Nonlinear least squares (NLS) provides the maximum likelihood estimate (MLE) of the anchor positions and their uncertainty. This allows to also provide an accuracy estimate for the resulting tag localization.