University of Oulu

L. Terças, C. H. M. de Lima, J. Saloranta and M. Latva-aho, "Hybrid Bayesian-based Indoor Localization Mechanisms for Distributed Antenna Systems," 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 2021, pp. 1-5, doi: 10.1109/VTC2021-Spring51267.2021.9448702

Hybrid Bayesian-based indoor localization mechanisms for distributed antenna systems

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Author: Terças, Leonardo1; de Lima, Carlos H. M.1; Saloranta, Jani1;
Organizations: 1Centre for Wireless Communications (CWC), University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021100850398
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-10-08
Description:

Abstract

This work proposes and evaluates a hybrid Bayesian-based localization method to estimate the position of a target node using received signal strength and time of flight measurements. In our investigations, we consider these measurements are acquired through a distributed antenna system which is connected to a common master anchor node. The baseline non-hybrid scenarios use only received signal strength measurements to estimate the position of interest, while the hybrid implementation combines time of arrival measurements as well. Both Bayesian-based (non) hierarchical approaches approximates the posterior distribution of the target’s location coordinates using Markov Chain Monte Carlo methods. The hierarchical method introduces conditional interdependencies to the model parameters, resulting in less model variance. Herein, the root mean square error is used to evaluate the performance of the indoor test scenarios. Our results show that both hybrid and hierarchical approaches outperform the baseline Bayesian model, while the former significantly increase the accuracy the target position estimate.

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Series: IEEE Vehicular Technology Conference
ISSN: 1090-3038
ISSN-L: 1090-3038
ISBN: 978-1-7281-8964-2
ISBN Print: 978-1-7281-8965-9
Article number: 9448702
DOI: 10.1109/VTC2021-Spring51267.2021.9448702
OADOI: https://oadoi.org/10.1109/VTC2021-Spring51267.2021.9448702
Host publication: 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring, 25-28 April 2021, Helsinki, Finland
Conference: IEEE Vehicular Technology Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: The research leading to these results has received funding from the Academy of Finland through the grants No. 318927 (project 6Genesis Flagship) and No. 24303208.
Academy of Finland Grant Number: 318927
24303208
Detailed Information: 318927 (Academy of Finland Funding decision)
24303208 (Academy of Finland Funding decision)
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