An Enhanced Mobile Device Based Navigation Model: Ubiquitous Computing

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Date
2018-01
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IGI Global
Abstract
Thisarticleformulated,simulatedandevaluatedanenhancedmodelforanon-linear/non-Gaussian integratedGlobalPositioningSystem(GPS)andInertialNavigationSystem(INS)mobile-baseddevice navigationsystemusingtheParticleFilter(PF).Thiswaswithaviewtoenhancingtheaccuracy andminimizethedelayexperiencedintheexistingsystemwhichreliesonlineardata.Anandroid drivenInfinixX5mobiledevicewithGPSandINS-basedsensorswasusedtoimplementthemodel formulated,standardBayesianestimatorswereusedtogeneratenon-lineardatasetswithGaussian/ non-GaussianwhitenoisesformobiledevicebasedINS/GPSsensors.Amathematicalmodelwas formulatedusingSamplingImportance-weightResampling(SIR)algorithmofthePF.Theconceptual modelwasdevelopedusingSimulinkandthedesignspecificationwasdoneusingUnifiedModeling Language(UML).ThemodelwassimulatedwithMATLABandthesimulationresultsobtainedwere evaluatedusingstandardmetrics,andbenchmarkedwithexistingmodel.Theoverallresultsshowed thattheproposedmodelperformedbetterthanexistingonesintermofaccuracy.However,themodel didnotimpactondelayreduction.
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TITLE:An Enhanced Mobile Device Based Navigation Model: Ubiquitous Computing VOLUME NO:9 ISSUE NO:2 JANUARY TO MARCH 2018 PAGES:23
Keywords
GPS, INS, Kalman Filter, Navigation, Particle, Re-Sampling, SIR
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