Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning

Detalhes bibliográficos
Autor(a) principal: Karmacharya, Amrit
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/10362/95137
Resumo: Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
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spelling Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioningSensor FusionKalman FilterBLE positioningIndoor PositioningSmartphoneDissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesGPS has been a de-facto standard for outdoor positioning. For indoor positioning different systems exist. But there is no general solution to fit all situations. A popular choice among service provider is BLE-based IPS. BLE-has low cost, low power consumption, and tit is are compatible with newer smartphones. These factors make it suitable for mass market applications with an estimated market of 10 billion USD by 2020. Although, BLEbased IPS have advantages over its counterparts, it has not solved the position accuracy problem yet. More research is needed to meet the position accuracy required for indoor LBS. In this thesis, two ways for accuracy improvement were tested i) a new algorithm for BLE-based IPS was proposed and ii) fusion of BLE position estimates with IMU position estimates was implemented. The first way exploits a concept from control survey called well-conditioned triangle. Theoretically, a well-conditioned triangle is an equilateral triangle but for in practice, triangles whose angles are greater than 30° and less than 120° are considered well-conditioned. Triangles which do not satisfy well-condition are illconditioned. An estimated position has the least error if the geometry from which it is estimated satisfy well-condition. Ill-conditioned triangle should not be used for position estimation. The proposed algorithm checked for well-condition among the closest detected beacons and output estimates only when the beacons geometry satisfied well-condition. The proposed algorithm was compared with weighted centroid (WC) algorithm. Proposed algorithm did not improve on the accuracy but the variance in error was highly reduced. The second way tested was fusion of BLE and IMU using Kálmán filter. Fusion generally gives better results but a noteworthy result from fusion was that the position estimates during turns were accurate. When used separately, both BLE and IMU estimates showed errors in turns. Fusion with IMU improved the accuracy. More research is required to improve accuracy of BLE-based IPS. Reproducibility self-assessment (https://osf.io/j97zp/): 2, 2, 2, 1, 2 (input data, prepossessing, methods, computational environment, results).Torres-Sospedra, JoaquínKray, ChristianCastelli, MauroRUNKarmacharya, Amrit2020-03-27T08:17:48Z2020-03-052020-03-05T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/95137TID:202464970enginfo: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:RCAAP2024-03-11T04:43:09Zoai:run.unl.pt:10362/95137Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:38:14.196565Repositório 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 Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
title Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
spellingShingle Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
Karmacharya, Amrit
Sensor Fusion
Kalman Filter
BLE positioning
Indoor Positioning
Smartphone
title_short Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
title_full Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
title_fullStr Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
title_full_unstemmed Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
title_sort Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning
author Karmacharya, Amrit
author_facet Karmacharya, Amrit
author_role author
dc.contributor.none.fl_str_mv Torres-Sospedra, Joaquín
Kray, Christian
Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Karmacharya, Amrit
dc.subject.por.fl_str_mv Sensor Fusion
Kalman Filter
BLE positioning
Indoor Positioning
Smartphone
topic Sensor Fusion
Kalman Filter
BLE positioning
Indoor Positioning
Smartphone
description Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
publishDate 2020
dc.date.none.fl_str_mv 2020-03-27T08:17:48Z
2020-03-05
2020-03-05T00:00:00Z
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/10362/95137
TID:202464970
url http://hdl.handle.net/10362/95137
identifier_str_mv TID:202464970
dc.language.iso.fl_str_mv eng
language eng
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
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