  Ultra-Wideband (UWB) systems are becoming increasingly popular for indoor
localization, where range measurements are obtained by measuring the
time-of-flight of radio signals. However, the range measurements typically
suffer from a systematic error or bias that must be corrected for high-accuracy
localization. In this paper, a ranging protocol is proposed alongside a robust
and scalable antenna-delay calibration procedure to accurately and efficiently
calibrate antenna delays for many UWB tags. Additionally, the bias and
uncertainty of the measurements are modelled as a function of the
received-signal power. The full calibration procedure is presented using
experimental training data of 3 aerial robots fitted with 2 UWB tags each, and
then evaluated on 2 test experiments. A localization problem is then formulated
on the experimental test data, and the calibrated measurements and their
modelled uncertainty are fed into an extended Kalman filter (EKF). The proposed
calibration is shown to yield an average of 46% improvement in localization
accuracy. Lastly, the paper is accompanied by an open-source UWB-calibration
Python library, which can be found at
https://github.com/decargroup/uwb_calibration.
