A GPS-aided Inertial Navigation System in Direct Configuration

This work presents a practical method fo r estimating the full kinema tic state of a vehicle, along with sensor error parameters, through the integration of inertial and GPS measurements. This ki nd of system for determining attitude and position of vehicles and craft (either manned or unmann ed) is...

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Detalles Bibliográficos
Autor: R. Munguía
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2014
País:México
Institución:Universidad de Guadalajara
Repositorio:Redalyc-UDG
OAI Identifier:oai:redalyc.org:47431860017
Acceso en línea:https://www.redalyc.org/articulo.oa?id=47431860017
Access Level:acceso abierto
Palabra clave:Ingeniería
Sensor Fusion
State Estimation
Inertial Navigation
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spelling A GPS-aided Inertial Navigation System in Direct ConfigurationR. MunguíaIngenieríaSensor FusionState EstimationInertial NavigationThis work presents a practical method fo r estimating the full kinema tic state of a vehicle, along with sensor error parameters, through the integration of inertial and GPS measurements. This ki nd of system for determining attitude and position of vehicles and craft (either manned or unmann ed) is essential for real time, guidance and navigation tasks, as well as for mobile robot applications. The architecture of the system is based in an Extended Kalman filtering approach in direct c onfiguration. In this case, the filter is explicitly derived from the ki nematic model, as well as from the mode ls of sensors error. The architecture has been designed in a manner that it permits to be easily modified, in order to be applied to vehicles with diverse dynamical behaviors. The estimated variables and parameters are: i) Attitude and bias-compensated rotational speed of the vehicle, ii) Position, velocity and bias-compensated acceleration of the vehicle and iii) bias of gyroscopes and accelerometers. Experimental results with real data show that the propos ed method is enough robust for its use along with low-cost sensors.Universidad Nacional Autónoma de México2014info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdf1665-6423https://www.redalyc.org/articulo.oa?id=47431860017Journal of Applied Research and Technology (México) Num.4 Vol.12reponame:Redalyc-UDGinstname:Universidad de Guadalajarainstacron:UDGenhttp://www.redalyc.org/revista.oa?id=474Journal of Applied Research and Technologyinfo:eu-repo/semantics/openAccessoai:redalyc.org:474318600172026-01-29T04:44:33Z
dc.title.none.fl_str_mv A GPS-aided Inertial Navigation System in Direct Configuration
title A GPS-aided Inertial Navigation System in Direct Configuration
spellingShingle A GPS-aided Inertial Navigation System in Direct Configuration
R. Munguía
Ingeniería
Sensor Fusion
State Estimation
Inertial Navigation
title_short A GPS-aided Inertial Navigation System in Direct Configuration
title_full A GPS-aided Inertial Navigation System in Direct Configuration
title_fullStr A GPS-aided Inertial Navigation System in Direct Configuration
title_full_unstemmed A GPS-aided Inertial Navigation System in Direct Configuration
title_sort A GPS-aided Inertial Navigation System in Direct Configuration
dc.creator.none.fl_str_mv R. Munguía
author R. Munguía
author_facet R. Munguía
author_role author
dc.subject.none.fl_str_mv Ingeniería
Sensor Fusion
State Estimation
Inertial Navigation
topic Ingeniería
Sensor Fusion
State Estimation
Inertial Navigation
description This work presents a practical method fo r estimating the full kinema tic state of a vehicle, along with sensor error parameters, through the integration of inertial and GPS measurements. This ki nd of system for determining attitude and position of vehicles and craft (either manned or unmann ed) is essential for real time, guidance and navigation tasks, as well as for mobile robot applications. The architecture of the system is based in an Extended Kalman filtering approach in direct c onfiguration. In this case, the filter is explicitly derived from the ki nematic model, as well as from the mode ls of sensors error. The architecture has been designed in a manner that it permits to be easily modified, in order to be applied to vehicles with diverse dynamical behaviors. The estimated variables and parameters are: i) Attitude and bias-compensated rotational speed of the vehicle, ii) Position, velocity and bias-compensated acceleration of the vehicle and iii) bias of gyroscopes and accelerometers. Experimental results with real data show that the propos ed method is enough robust for its use along with low-cost sensors.
publishDate 2014
dc.date.none.fl_str_mv 2014
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dc.identifier.none.fl_str_mv 1665-6423
https://www.redalyc.org/articulo.oa?id=47431860017
identifier_str_mv 1665-6423
url https://www.redalyc.org/articulo.oa?id=47431860017
dc.language.none.fl_str_mv en
language_invalid_str_mv en
dc.relation.none.fl_str_mv http://www.redalyc.org/revista.oa?id=474
dc.rights.none.fl_str_mv Journal of Applied Research and Technology
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Journal of Applied Research and Technology
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional Autónoma de México
publisher.none.fl_str_mv Universidad Nacional Autónoma de México
dc.source.none.fl_str_mv Journal of Applied Research and Technology (México) Num.4 Vol.12
reponame:Redalyc-UDG
instname:Universidad de Guadalajara
instacron:UDG
instname_str Universidad de Guadalajara
instacron_str UDG
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reponame_str Redalyc-UDG
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