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抗差EKF滤波在GNSSINS组合导航中的应用.docx

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抗差EKF滤波在GNSSINS组合导航中的应用 Title:ApplicationofRobustEKFFilteringinGNSS-INSIntegrationforNavigation Abstract: TheintegrationofGlobalNavigationSatelliteSystems(GNSS)andInertialNavigationSystems(INS)hasgainedsignificantattentioninthefieldofnavigationduetothecomplementaryadvantagesofthesesystems.However,thenavigationsolutionderivedfromtheintegrationmaysufferfromerrorscausedbyoutliers,noise,andbiases.Inthispaper,wepresenttheapplicationofrobustExtendedKalmanFilter(EKF)filteringintheGNSS-INSintegrationtomitigatetheinfluenceofoutliersanduncertainties,enhancingtheaccuracyandreliabilityofthenavigationsolution.Wediscusstheprinciples,advantages,andchallengesoftherobustEKFfilteringtechniqueanddemonstrateitseffectivenessthroughsimulationresults. 1.Introduction: TheGNSS-INSintegratednavigationsystemcombinestheadvantagesofGNSS'sabsolutepositionmeasurementandINS'scontinuousnavigationsolutiontoprovideaccurateandreliablenavigationundervariousoperationalscenarios.However,theaccurateestimationofnavigationparameters,suchasposition,velocity,andattitude,isessentialforthesuccessfulintegrationofthesesystems.TherobustEKFfilteringtechniquehasemergedasaneffectivesolutiontohandleuncertainties,biases,andoutlierspresentinthemeasurementsobtainedfromGNSSandINSsensors.ThispaperaimstoinvestigatetheapplicationoftherobustEKFfilteringtechniqueintheGNSS-INSintegrationfornavigationimprovement. 2.RobustEKFFiltering: 2.1Principles: TheExtendedKalmanFilter(EKF)iswidelyusedforstateestimationinnavigationsystems.However,thetraditionalEKFissensitivetomeasurementoutliersandmodeluncertainties,whichcandegradetheaccuracyandreliabilityoftheestimatedstates.TherobustEKFfilter,alsoknownastherobustifiedEKF,addressesthisissuebyincorporatingrobustestimationtechniques. TherobustEKFfilteringtechniqueusesaweightedleastsquaresframeworktoupdatethestateestimateiteratively.Theweightsarederivedbasedonrobustestimationtheory,whichdownweightstheinfluenceofoutliersandincreasestherobustnessofthefilter.Thisfilteringtechniquemodelsmeasuremen