Shareef, A. A., Kaur, J. , Imran, M. A. , Ali, H. T. M., Abbasi, Q. H. and Abbas, H. T. (2023) A Statistical Analysis of Feature Transformation for Efficient Localisation in Urban Environments. In: 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Portland, Oregon, USA, 23–28 July 2023, pp. 269-270. ISBN 9781665442282 (doi: 10.1109/USNC-URSI52151.2023.10238286)
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Abstract
In this paper, we perform a transformation-based statistical analysis with an eye to designing a robust and efficient localisation scheme. To this end, we evaluate the coefficient of determination (COD) also denoted as R2 on simulated electromagnetic wave propagation models in an urban environment. Our transformation-based statistical models show that two measurable network parameters, namely the received power (RP) and the time of arrival (ToA), present a strong correlation with a mobile user's given location. By transforming the network parameters we were able to achieve COD of 0.577 for the RP and 0.549 for ToA using the Modulus transformation. We believe that by exploiting the high correlation of parameter transformation, there is potential to design fast and robust machine learning localisation schemes through which the future location of a mobile user can be accurately and reliably predicted.
| Item Type: | Conference Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Imran, Professor Muhammad and Abbas, Dr Hasan and Abbasi, Professor Qammer and Kaur, Jaspreet |
| Authors: | Shareef, A. A., Kaur, J., Imran, M. A., Ali, H. T. M., Abbasi, Q. H., and Abbas, H. T. |
| College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
| ISSN: | 1947-1491 |
| ISBN: | 9781665442282 |
| Published Online: | 07 September 2023 |
| Copyright Holders: | Copyright © 2023 IEEE |
| First Published: | First published in 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting: 269-270 |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
| Related URLs: |
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