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.
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.
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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.
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44
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3
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 21, 2024
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