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Error Mitigation for TDoA UWB Indoor Localization using Unsupervised Machine Learning
Indoor positioning systems based on Ultra-wideband (UWB) technology are gaining recognition for their ability to provide cm-level localization accuracy.
Removing the need for ground truth UWB data collection: self-supervised ranging error correction using deep reinforcement learning
A reinforcement learning agent uses the channel impulse response as a state and predicts corrections to minimize the error between corrected and estimated ranges.
A Comprehensive Overview on UWB Radar: Applications, Standards, Signal Processing Techniques, Datasets, Radio Chips, Trends and Future Research Directions
The goal of this survey is to provide a comprehensive view of the technical fundamentals and emerging trends in UWB radar.
Feature-Based Generalized Gaussian Distribution Method for NLoS Detection in Ultra-Wideband (UWB) Indoor Positioning System
However, it is difficult for existing ML approaches to maintain a high classification accuracy when the database contains a small number of NLoS signals and a large number of Line-of-Sight (LoS) signals.
Deep reinforcement learning for automatic run-time adaptation of UWB PHY radio settings
To address this, we propose a deep Q-learning approach for enabling reliable UWB communication, maximizing packet reception rate (PRR) and minimizing energy consumption.
An Overview of Ultra-WideBand (UWB) Standards and Organizations (IEEE 802.15.4, FiRa, Apple): Interoperability Aspects and Future Research Directions
In this paper, the fundamentals of UWB compatibility are investigated by first giving an overview of different UWB radio chips on the market.
