13599.基于footmounted的imu室內(nèi)行人航跡推算研究

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3、(保密的學位論文在解密后適用本授權書)學位論文作者簽名(手寫)：從2，導師簽名(手寫)：研私簽字日期：加7聲歲月弓JIEI簽字日期：∞l弓年廠月弓f諺AbstractABSTRACTWiththerapiddevelopmentofmodemscienceandtechnologypeoplehasthegraterequiresofpositioningandnavigationincreasinglyespeciallyinindo

4、orenvironment，suchasmarket、library、parkingareaandmine，whichusuallyneedstealizethepositioninformationofusersordevicesrapidlyandaccuratelyHoweverasradiopropagationisaffectedbyfade、multipathanddisturbincomplexindooritisdiff

5、iculttoensuretheaccuracyandstabilityofcollectedsignalcharacteristicsTherefore，thepositioningtechnologiesbasedonsomewirelessnetworks(suchasWiFiandZigBeelcan’tcurrentlyguaranteethepositionprecisionsteadilyandrightlyinallen

6、vironmentInertialMeasureUnit(IMU)isautonomousandfreefromtheoutsideinfluence，SOthatitattractsextensiveattentionsandintensiveresearchinnavigationfieldsInthispaperthethemeisIMUindoorPedestrianDeadReckoning(PDR)Mainresearchi

7、sthetheory、simulationandperformanceanalysisofMicro—ElectroMechanicalSystems(MEMS)IMUindoorPDRalgorithm，whichismainlyfocusedonthefollowingthreeaspects：1MEMSIMUinitialalignment：ithasagreatimportantplaceinnavigationalgorith

8、m，whichwilldirectlyaffecttheaccuracyofnavigationparametersAsthehardwareperformancelimitationofMEMSIMU，ithaslowalignmentprecision、析thMEMSIMUaloneespeciallyinheadingSointhispaperamethodisdiscussedbasedoninformationfusionof

9、magnetometersensorandMEMSIMU，andcompletesMEMSIMUinitialalignment；2Pedestrianmotionmodel：IMUstanceisthekeyissuesinindoorPDRalgorithm，whichdeterminestheusingofobservationaccmatelyinExtendedKalmanFilter(EKF)Therefore，pedest

10、rianmotionmodelispresented淅tllaccelerometersandgyroscopesforIMUstancedetectioneffectivelyinthispaperItestimatestheerrorsofnavigationparametersandsensorsexactlyandcompensatesinstantlybasedonfoot—mountedandEKFwhendetectedI