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Wireless localisation is becoming increasingly important in various applications such as smart homes, elderly healthcare facilities and in industry where centimetre localisation accuracy is desired. Ultra-wideband (UWB) systems can be used for such applications since they can achieve a ranging precision below 10 cm in a Line-of-Sight (LoS) setup. However, in non LoS (NLoS) scenarios these systems provide a lower accuracy. In this paper, we exploit the high resolution Channel Impulse Response (CIR) provided by the Decawave EVK1000 boards for localisation in a residential environment. We employ a single anchor node and use the CIR obtained from five different locations as fingerprints to investigate whether the location of the tag can be accurately estimated in NLoS scenarios. Our investigation showed that the CIR can be effectively used as fingerprints to provide a location classification accuracy as high as 98% when the environment remains relatively stable. However, using the CIR data recorded in a second experiment (same setup as first experiment) as test data and applying the trained model of the first experiment on it showed a significant degradation in performance (50-60% accuracy) since there were changes in the environment. On the other hand, by using five features extracted from the UWB signals for location classification, an accuracy in excess of 99% is obtained during testing in both experiments.
|Title of host publication||2020 IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan, 2020|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||6|
|Publication status||Accepted/In press - 17 Aug 2020|
- Digital Health