A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments

Bibliographic Details
Main Author: Tomic, Slavisa
Publication Date: 2017
Other Authors: Beko, Marko, Dinis, Rui, Carvalho, Paulo Montemuza
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/11144/3641
Summary: This letter addresses the problem of target localization in harsh indoor environments based on range measurements. To mitigate the non-line-of-sight (NLOS) bias, we propose a novel robust estimator by transforming the localization problem into a generalized trust region sub-problem framework. Although still non-convex in general, this class of problems can be readily solved exactly by means of bisection procedure. The new approach does not require to make any assumptions about the statistics of NLOS bias, nor to try to distinguish which links are NLOS and which are not. Unlike the existing algorithms, the computational complexity of the proposed algorithm is linear in the number of reference nodes. Our simulation results corroborate the effectiveness of the new algorithm in terms of NLOS bias mitigation and show that the performance of our estimator is highly competitive with the performance of the stateof-the-art algorithms. In fact, they show that the novel estimator outperforms slightly the existing ones in general, and that it always provides a feasible solution
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spelling A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS EnvironmentsRobust LocalizationTime of Arrival (TOA),Non-Line-of-Sight (NLOS)Generalized Trust Region Sub-Problem (GTRS)Wireless Sensor Network (WSN).This letter addresses the problem of target localization in harsh indoor environments based on range measurements. To mitigate the non-line-of-sight (NLOS) bias, we propose a novel robust estimator by transforming the localization problem into a generalized trust region sub-problem framework. Although still non-convex in general, this class of problems can be readily solved exactly by means of bisection procedure. The new approach does not require to make any assumptions about the statistics of NLOS bias, nor to try to distinguish which links are NLOS and which are not. Unlike the existing algorithms, the computational complexity of the proposed algorithm is linear in the number of reference nodes. Our simulation results corroborate the effectiveness of the new algorithm in terms of NLOS bias mitigation and show that the performance of our estimator is highly competitive with the performance of the stateof-the-art algorithms. In fact, they show that the novel estimator outperforms slightly the existing ones in general, and that it always provides a feasible solutionIEEE2018-04-11T16:30:36Z2017-01-01T00:00:00Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/11144/3641eng10.1109/LCOMM.2017.2737985Tomic, SlavisaBeko, MarkoDinis, RuiCarvalho, Paulo Montemuzainfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-08-01T02:01:09Zoai:repositorio.ual.pt:11144/3641Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:40:20.581587Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
title A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
spellingShingle A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
Tomic, Slavisa
Robust Localization
Time of Arrival (TOA),
Non-Line-of-Sight (NLOS)
Generalized Trust Region Sub-Problem (GTRS)
Wireless Sensor Network (WSN).
title_short A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
title_full A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
title_fullStr A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
title_full_unstemmed A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
title_sort A Robust Bisection-based Estimator for TOA-based Target Localization in NLOS Environments
author Tomic, Slavisa
author_facet Tomic, Slavisa
Beko, Marko
Dinis, Rui
Carvalho, Paulo Montemuza
author_role author
author2 Beko, Marko
Dinis, Rui
Carvalho, Paulo Montemuza
author2_role author
author
author
dc.contributor.author.fl_str_mv Tomic, Slavisa
Beko, Marko
Dinis, Rui
Carvalho, Paulo Montemuza
dc.subject.por.fl_str_mv Robust Localization
Time of Arrival (TOA),
Non-Line-of-Sight (NLOS)
Generalized Trust Region Sub-Problem (GTRS)
Wireless Sensor Network (WSN).
topic Robust Localization
Time of Arrival (TOA),
Non-Line-of-Sight (NLOS)
Generalized Trust Region Sub-Problem (GTRS)
Wireless Sensor Network (WSN).
description This letter addresses the problem of target localization in harsh indoor environments based on range measurements. To mitigate the non-line-of-sight (NLOS) bias, we propose a novel robust estimator by transforming the localization problem into a generalized trust region sub-problem framework. Although still non-convex in general, this class of problems can be readily solved exactly by means of bisection procedure. The new approach does not require to make any assumptions about the statistics of NLOS bias, nor to try to distinguish which links are NLOS and which are not. Unlike the existing algorithms, the computational complexity of the proposed algorithm is linear in the number of reference nodes. Our simulation results corroborate the effectiveness of the new algorithm in terms of NLOS bias mitigation and show that the performance of our estimator is highly competitive with the performance of the stateof-the-art algorithms. In fact, they show that the novel estimator outperforms slightly the existing ones in general, and that it always provides a feasible solution
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01T00:00:00Z
2017
2018-04-11T16:30:36Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/11144/3641
url http://hdl.handle.net/11144/3641
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/LCOMM.2017.2737985
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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