UWB system and algorithms for indoor positioning

Detalhes bibliográficos
Autor(a) principal: Yuankang Gao
Data de Publicação: 2020
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/21671
Resumo: This research work presents of study of ultra-wide band (UWB) indoor positioning considering different type of obstacles that can affect the localization accuracy. In the actual warehouse, a variety of obstacles including metal, board, worker and other obstacles will have NLOS (non-line-of-sight) impact on the positioning of the logistics package, which influence the measurement of the distance between the logistics package and the anchor , thereby affecting positioning accuracy. A new developed method attempts to improve the accuracy of UWB indoor positioning, through and improved positioning algorithm and filtering algorithm. In this project, simulate the warehouse environment in the laboratory, several simulation proves that the used Kalman filter algorithm and Markov algorithm can effectively reduce the error of NLOS. Experimental validation is carried out considering a mobile tag mounted on a robot platform.
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spelling UWB system and algorithms for indoor positioningUWBIndoor positioningKalman filter algorithmMarkov algorithmPosicionamento internoAlgoritmo de filtro KalmanAlgoritmo de MarkovPlataformas móveis de tipo robôThis research work presents of study of ultra-wide band (UWB) indoor positioning considering different type of obstacles that can affect the localization accuracy. In the actual warehouse, a variety of obstacles including metal, board, worker and other obstacles will have NLOS (non-line-of-sight) impact on the positioning of the logistics package, which influence the measurement of the distance between the logistics package and the anchor , thereby affecting positioning accuracy. A new developed method attempts to improve the accuracy of UWB indoor positioning, through and improved positioning algorithm and filtering algorithm. In this project, simulate the warehouse environment in the laboratory, several simulation proves that the used Kalman filter algorithm and Markov algorithm can effectively reduce the error of NLOS. Experimental validation is carried out considering a mobile tag mounted on a robot platform.Este trabalho de pesquisa apresenta um estudo de posicionamento de banda ultra-larga (UWB) em ambientes internos considerando diferentes tipos de obstáculos que podem afetar a precisão de localização. No armazém real, uma variedade de obstáculos incluindo metal, placa, trabalhador e outros obstáculos terão impacto NLOS (não linha de visão) no posicionamento do pacote logístico, o que influencia a medição da distância entre o pacote logístico e a âncora, afetando assim a precisão do posicionamento. Um novo método desenvolvido tenta melhorar a precisão do posicionamento interno UWB, através de um algoritmo de posicionamento e algoritmo de filtragem aprimorados. Neste projeto, para simular o ambiente de warehouse em laboratório, diversas simulações comprovam que o algoritmo de filtro de Kalman e o algoritmo de Markov usados podem efetivamente reduzir o erro de NLOS. A validação experimental é realizada considerando um tag móvel montado em uma plataforma de robô.2021-01-29T11:43:06Z2020-12-22T00:00:00Z2020-12-222020-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/21671TID:202578399engYuankang Gaoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:31:31Zoai:repositorio.iscte-iul.pt:10071/21671Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:14:11.245472Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv UWB system and algorithms for indoor positioning
title UWB system and algorithms for indoor positioning
spellingShingle UWB system and algorithms for indoor positioning
Yuankang Gao
UWB
Indoor positioning
Kalman filter algorithm
Markov algorithm
Posicionamento interno
Algoritmo de filtro Kalman
Algoritmo de Markov
Plataformas móveis de tipo robô
title_short UWB system and algorithms for indoor positioning
title_full UWB system and algorithms for indoor positioning
title_fullStr UWB system and algorithms for indoor positioning
title_full_unstemmed UWB system and algorithms for indoor positioning
title_sort UWB system and algorithms for indoor positioning
author Yuankang Gao
author_facet Yuankang Gao
author_role author
dc.contributor.author.fl_str_mv Yuankang Gao
dc.subject.por.fl_str_mv UWB
Indoor positioning
Kalman filter algorithm
Markov algorithm
Posicionamento interno
Algoritmo de filtro Kalman
Algoritmo de Markov
Plataformas móveis de tipo robô
topic UWB
Indoor positioning
Kalman filter algorithm
Markov algorithm
Posicionamento interno
Algoritmo de filtro Kalman
Algoritmo de Markov
Plataformas móveis de tipo robô
description This research work presents of study of ultra-wide band (UWB) indoor positioning considering different type of obstacles that can affect the localization accuracy. In the actual warehouse, a variety of obstacles including metal, board, worker and other obstacles will have NLOS (non-line-of-sight) impact on the positioning of the logistics package, which influence the measurement of the distance between the logistics package and the anchor , thereby affecting positioning accuracy. A new developed method attempts to improve the accuracy of UWB indoor positioning, through and improved positioning algorithm and filtering algorithm. In this project, simulate the warehouse environment in the laboratory, several simulation proves that the used Kalman filter algorithm and Markov algorithm can effectively reduce the error of NLOS. Experimental validation is carried out considering a mobile tag mounted on a robot platform.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-22T00:00:00Z
2020-12-22
2020-11
2021-01-29T11:43:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/21671
TID:202578399
url http://hdl.handle.net/10071/21671
identifier_str_mv TID:202578399
dc.language.iso.fl_str_mv eng
language eng
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.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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