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- W2185448072 abstract "Theintegrated navigation system, specially the systembasedon GPS andINS,isa leading trendof navigation technology , andsomeoftypical integrated navigation systems havebeendeveloped andtested inthe pastfewyears(FAR,98). Butduetothecomplex application circumstance, itisdifficult todescribe thenoise statistical property accurately. Inthis paper,amodified adaptive filter algorithm ispresented forINS/GPSIntegrated Navigation system. Atfirst, aimproved Kalmanfilter andHoorobust filter areexplicitly represented forINS/GPSIntegrated Navigation system. Meanwhile, anstandard forjudging that whetherthefilter trendstodivergence isproposed to combinethe two methods.Aimingat the detail position/velocity integrated mode,thecomputer simulation result ofINS/GPSintegrated navigation showthatthis methodcanrestrain thedivergence effectively andhasbetter adaptive ability. H robust filter, adaptive filter I.INTRODUCTION Integrated navigation system hasbeenbecoming themain direction ofthedevelopment ofnavigation andguidance technology, inparticular, theINS/GPSintegrated system isbeing given muchattention inthepast fewyears. When combinedtogether, GPS and INS provide many complimentary characteristics thatovercomethe limitations experienced when usingeachsensor individually. Theadvantages ofcombining thelong-term accuracy oftheGlobal Positioning System (GPS) withthe short-term stability ofanautonomous Inertial Navigation System(INS)havebeenextensively investigated in published literature. Theyinclude thelimiting ofinertial position andvelocity errors, theinitial alignment ofgyros andaccelerometers, theestimation ofinertial systemic errors, theability toair-alignment theINSusing GPS measurements, andtheaiding oftheGPSbytheINS during aircraft fiercely maneuvering andsatellite outages. Thetraditional INS/GPSintegration istypically carried outthrough Kalmanfilter. Kalmanfiltering hasbecome a wholesystem during theprocedure ofitsdevelopment, anditsalgorithm isalready being usedinmanyfields, especially inintegrated navigation system. But,the traditional Kalmanfilter isbuiltaccording to H2 estimation criterion, only whenthecharacteristics ofthe extend noise signals andthesystem dynamics areknown, its performance canbepreserved. But,inmanyfield, the statistic models oftheextend noises aredifficult tobuild. Atthesametime, thesystem dynamics maybeuncertain. SoKalmanfilter will beinvalid atsometime. Because of these reasons, theadaptive filtering androbust filtering theory isbroughtand developed inthelast decade. Inthis paper, anadaptive filter namedSage-Husa andHoo robust filter arediscussed basedonthemathematic description ofeachother. Meanwhile, a criterion is proposed forcombining theSage-Husa filter andH°° robust filter. Attheendofthis paper, this novel method is applied inthefield ofINS/GPSIntegrated Navigation System." @default.
- W2185448072 created "2016-06-24" @default.
- W2185448072 creator A5038749014 @default.
- W2185448072 date "2006-01-01" @default.
- W2185448072 modified "2023-09-27" @default.
- W2185448072 title "AnAdaptive Filter forINS/GPSIntegrated Navigation System" @default.
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