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基于海流数据库的Kalman滤波在水下导航中的应用(英文).docx

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基于海流数据库的Kalman滤波在水下导航中的应用(英文) Introduction: Underwaternavigationhasbeenachallengingfieldformanyyears.Variousnavigationsystemshavebeendevelopeddependingonthespecificapplication.Amongthem,theuseofoceancurrentsfornavigationhasgainedprominenceinrecentyears.Thismethodleveragesthefactthatoceancurrentsflowinpredictablepatterns,andtheircharacteristicscanbeusedtoestimatethepositionofanunderwatervehicle.ThemostsignificantadvantageofthisapproachisthatitdoesnotuseanyexternalreferencessuchasGPSoracousticsignals,whichcanbeeasilyjammedordisturbed.However,theoceancurrentdatabaseisnoterror-free,andthemeasurementsacquiredbyunderwatervehiclesarealsosubjecttonoise.Therefore,itisnecessarytouseaproperfilteringmethodtoestimatethevehicle'spositionaccurately.Kalmanfiltershavebeenwidelyusedinvariousapplications,includingunderwaternavigation.Inthispaper,wewilldiscussKalmanfilteringforunderwaternavigationusingtheoceancurrentdatabaseasthesourceofinformation. OceanCurrentDatabase: Oceancurrentsarethecontinuous,directedmovementofseawatergeneratedbyvariousforceslikewind,tides,andearth'srotation.Thesecurrentscanflowforthousandsofmilesandaffecttheclimateandweatherpatternsaroundtheworld.Oceanographershavebeenstudyingoceancurrentsfordecades,andtheyhavedevelopedacomprehensivedatabasethatcontainsinformationregardingthedirectionandvelocityofoceancurrentsatdifferentdepthsandlocations.Theoceancurrentdatabaseisaninvaluablesourceofdataforunderwaternavigationbecauseitprovidesaccurateinformationonthephysicalcharacteristicsofoceancurrents.Thedataisregularlyupdated,ensuringthatitremainsrelevantanduseful. KalmanFiltering: Kalmanfilteringisanestimationtechniquethatusesaseriesofmeasurementstorefinepredictionsofasystem'sstate.Itiswidelyusedinnavigation,controlsystems,andsignalprocessing.TheKalmanfilterusesamathematicalmodelofthesystembeingestimatedandcombinesitwithmeasurementstoprovideanaccurateestimateofthesystem'sstate.Thefilterdynamicallyupdatesthestateestimateandpredictionasnewmeasurementsbecomeavailable. Kalman