Quadrature Kalman Filter （QKF） and Reduced Quadrature Kalman Filter （R-QKF） in Ballistic Target Tracking-中国期刊网

摘要 Recentlytherehavebeenresearchesaboutnewefficientnonlinearfilteringtechniques[1]~[3]inwhichthenonlinearfiltersgeneralizeelegantlytononlinearsystemswithouttheburdensomelinearizationsteps.Thus,truncationerrorsduetolinearizationcanbecompensated.ThesefiltersincludetheunscentedKalmanfilter(UKF),thecentraldifferencefilter(CDF)andthedivideddifferencefilter(DDF),andtheyarealsocalledSigmaPointFilters(SPFs)inaunifiedway[4].Forhigherorderapproximationofthenonlinearfunction.ItoandXiong[6]introducedanalgorithmcalledtheGaussHermiteFilter,whichisrevisitedin[5].TheGaussHermiteFiltergivesbetterapproximationattheexpenseofhighercomputationburden,althoughit’slessthantheparticlefilter.TheGaussHermiteFilterisusedasintroducedin[5]withadditionalpruningstepbyaddingthresholdfortheweightstoreducethequadraturepoints.

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Quadrature Kalman Filter （QKF） and Reduced Quadrature Kalman Filter （R-QKF） in Ballistic Target Tracking

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Quadrature Kalman Filter （QKF） and Reduced Quadrature Kalman Filter （R-QKF） in Ballistic Target Tracking

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