Improving Ultra Wideband Indoor UWB Indoor Localization Via Per-Anchor Bias Calibration and Reliability-Weighted Multilateration

Temidayo Oluwafunke  Otunniyi

doi:10.29284/gr2ztf67

Authors

Temidayo Oluwafunke Otunniyi Department of Electrical Engineering, Faculty of Engineering and Technology, Vaal University of Technology, South Africa.

DOI:

https://doi.org/10.29284/gr2ztf67

Keywords:

UWB; indoor localization; multilateration; calibration; reliability weighting; bootstrap; tail risk; RTLS.

Abstract

Ultra-wideband (UWB) ranging can provide accurate indoor localization, yet practical deployments exhibit substantial anchor-to-anchor heterogeneity caused by hardware-dependent timing offsets and environment-dependent ranging noise. This paper investigates a calibration strategy that explicitly separates these two effects: per-anchor systematic bias is estimated and removed, while anchor reliability is represented through inverse-variance weighting in the multilateration objective. The study uses 1,423 ranging packets collected from 17 anchors observing a stationary tag at a surveyed reference position. To prevent information leakage, packets are independently split 50/50 per anchor into calibration and evaluation subsets. Performance is assessed using 300 bootstrap trials. Relative to equal-weight multilateration, calibrated reliability-weighted multilateration reduces mean position error from 0.511 m to 0.244 m (52.3%) and median error from 0.469 m to 0.119 m (74.6%). However, the 90th-percentile error increases from 0.832 m to 1.031 m (23.9%). The key finding is therefore a distributional trade-off rather than a simple accuracy gain: calibration strongly improves typical fixes but can increase tail risk when calibration-period variance estimates are uncertain. The figures demonstrate this mechanism directly by linking anchor-level bias/noise heterogeneity to the observed localization-error distribution.

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