研究成果

Activity Sequence-Based Indoor Pedestrian Localization Using Smartphones

期刊名称: IEEE Transactions on Human-Machine Systems
全部作者: Baoding Zhou *,Qingquan Li ,Qingzhou Mao ,Wei Tu ,Xing Zhang
出版年份: 2015
卷       号: 45
期       号: 5
页       码: 562 - 574
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Thispaperpresentsanactivitysequence-basedin-doorpedestrianlocalizationapproachusingsmartphones.Theactivitysequenceconsistsofseveralcontinuousactivitiesduringthewalkingprocess,suchasturningatacorner,takingtheelevator,takingtheescalator,andwalkingstairs.Theseactivitiestakeplacewhenauserwalksatsomespecialpointsinthebuilding,likecorners,elevators,escalators,andstairs.Thespecialpointsformanindoorroadnetwork.Inourapproach,wefirstdetecttheuser’sactivitiesusingthebuilt-insensorsinasmartphone.Thedetectedactivitiesconstitutetheactivitysequence.Meanwhile,theuser’strajectoryisreckonedbyPedestrianDeadReckoning(PDR).Basedonthedetectedactivitysequenceandreckonedtrajectory,werealizepedestrianlocalizationbymatchingthemtotheindoorroadnetworkusingaHiddenMarkovModel.Afterencounteringseveralspecialpoints,thelocationoftheuserwouldconvergeonthetrueone.Weevaluateourproposedapproachusingsmartphonesintwobuildings:anofficebuildingandashoppingmall.Theresultsshowthattheproposedapproachcanrealizeautonomouspedestrianlocalizationevenwithoutknowingtheinitialpointintheenvironments.Themeanofflinelocalizationerrorisabout1.3m.TheresultsalsodemonstratethattheproposedapproachisrobusttoactivitydetectionerrorandPDRestimationerror.