KlemenBr/uwb_positioning

The code contains the preprocessing scripts and experiments that work on UWB Positioning and Tracking Data Set. The code demonstrate the UWB positioning technique with ranging error mitigation using deep learning-based ranging error estimation by convolutional neural networks (CNN) using TensorFlow deep learning platform.

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Emerging

This project helps researchers and engineers evaluate Ultra-Wideband (UWB) indoor positioning systems. It takes raw UWB ranging and tracking data and applies deep learning to mitigate ranging errors. The output is a more accurate position estimate for UWB systems, ideal for those working on precise indoor location tracking.

No commits in the last 6 months.

Use this if you are developing or evaluating UWB indoor positioning systems and need to assess or improve their accuracy by mitigating ranging errors using deep learning.

Not ideal if you are looking for a pre-built, production-ready UWB positioning solution or if you are not comfortable working with command-line tools and Docker.

indoor-positioning UWB-tracking localization-accuracy ranging-error-mitigation wireless-sensing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 7 / 25

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Stars

44

Forks

3

Language

Python

License

Apache-2.0

Last pushed

Mar 21, 2024

Commits (30d)

0

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