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区间Kalman滤波器及其在GPSINS组合导航系统中的应用(英文).docx

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区间Kalman滤波器及其在GPSINS组合导航系统中的应用(英文) Introduction: Inmodernnavigationsystems,theintegrationofGlobalPositioningSystem(GPS)andInertialNavigationSystem(INS)havebecomeanattractiveoption.Thisintegrationcanimprovetheaccuracyandreliabilityofthenavigationsystem,especiallyinsituationswhereGPSsignalsmaybeblockedordegraded.However,themajorchallengeinintegratingthesetwosystemsistodevelopareliablefilteringalgorithmthatcanaccuratelyestimatetheposition,velocity,andattitudeofthenavigationsystemundervariousoperatingconditions.Inthispaper,wepresenttheIntervalKalmanFilteranditsapplicationinGPS-INSintegratednavigationsystem. IntervalKalmanFilter: TheIntervalKalmanFilterisastateestimationalgorithmthatwasfirstintroducedbyJaulinetal.in2001.ItisanextensionofthelinearKalmanFilterandisdesignedtohandlenon-linearmeasurementmodelsanduncertainnoises.ThebasicideaofIntervalKalmanFilteristorepresenttheuncertainparametersofthemeasurementandstatemodelsasintervals,andthentopropagatetheseintervalsthroughthefilterrecursion.Thisallowsustoobtainanestimatorthatgivesaguaranteedboundingintervalforthestateofthesystem. InIntervalKalmanFilter,theinterval-valuedmeasurementmodelisrepresentedas: y=h(x)±δ whereyisthemeasurementvector,xisthestatevector,h(x)isthenon-linearmeasurementfunction,andδistheintervalnoise.Thestateestimationisperformedbypropagatingtheintervalnoisethroughthefilterrecursion,whichconsistsofthepredictorandupdatersteps.Thepredictorsteppredictsthestateintervalbasedonthesystemdynamicsandthepreviousstateinterval.Theupdaterstepupdatesthestateintervalbasedonthemeasurementinterval. ApplicationinGPS-INSIntegratedNavigationSystem: GPSandINSbothhavetheirownstrengthsandweaknessesintermsofaccuracyandreliability.GPSprovidesaccuratepositionandvelocityinformation,butitmaybeaffectedbysignalblockageormultipathpropagation.INSprovidesreliablemeasurementoftheattitudeandvelocity,butitspositionestimationmaydriftovertimeduetosensorerrorsandinitialpositioningerrors.Therefore,theintegrationofGPSandINScanimprovetheaccuracya