Debiasing of position estimations of UWB-based TDoA indoor positioning system

Debiasing of position estimations of UWB-based TDoA indoor positioning system

Title: Debiasing of position estimations of UWB-based TDoA indoor positioning system
Authors: Paolo Grasso (Autonomous Vehicles & Artificial Intelligence Laboratory Research Institute for Future Transport and Cities, Coventry University); Mauro S. Innocente (Autonomous Vehicles & Artificial Intelligence Laboratory Research Institute for Future Transport and Cities, Coventry University);
Year: 2020
Citation: Grasso, P., Innocente, M. S., (2020). Debiasing of position estimations of UWB-based TDoA indoor positioning system. UKRAS20 Conference: “Robots into the real world” Proceedings, 114-116.

https://doi.org/10.31256/Ua2Vp3X

Abstract:

When localising an object in a confined environment using an indoor positioning system (IPS) based on ultra-wideband (UWB) technology and an asynchronous time difference of arrival (TDoA) algorithm, systematic errors do occur. Theoretical estimation of these errors can be very hard to make. This study introduces a novel filtering algorithm for reducing the bias of position estimations, therefore increasing their accuracy. The problem is tackled for a two-dimensional IPS by formulating a debiasing filter using statistics of real data. Generalisation to the three-dimensional case should be straightforward.

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