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改进UKF算法在天波超视距雷达中的应用.docx

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改进UKF算法在天波超视距雷达中的应用 Title:ImprovingtheApplicationoftheUnscentedKalmanFilterAlgorithminBeyondLine-of-SightRadarSystems Abstract: BeyondLine-of-Sight(BLOS)radarsystems,suchastheover-the-horizonorskywaveradar,playavitalroleinlong-rangetargetdetectionandtracking.Thesesystemsfacenumerouschallengesincludingthepresenceofclutter,multipathpropagation,andhighmeasurementuncertainties.Toaddressthesechallenges,theUnscentedKalmanFilter(UKF)algorithmhasgainedsignificantattentionduetoitsabilitytohandlenon-linearsystems.ThispaperaimstoexploretheapplicationoftheUKFalgorithminBLOSradarsystemsandproposeimprovementstoenhanceitsperformance. 1.Introduction TheintroductionprovidesanoverviewoftheimportanceofBLOSradarsystemsandthechallengestheyface.Italsohighlightstheneedforrobustestimationalgorithms,suchastheUKF,toaccuratelypredictandtracktargetsinsuchsystems. 2.Background ThissectionprovidesabriefexplanationoftheUKFalgorithm,includingtheprocessofstateestimationandvariabletransformation.ItalsodiscussesthelimitationsoftraditionalKalmanfilteringalgorithmsinhandlingnon-linearsystemsandhowtheUKFalgorithmprovidesamoreaccurateestimation. 3.ApplicationofUKFinBLOSRadarSystems ThissectiondelvesintothespecificapplicationoftheUKFalgorithminBLOSradarsystems.Itdiscussesthestepsinvolvedintargettracking,includingtargetdetection,clutterfiltering,andestimationinitialization.ItalsopresentsanoverviewofthemeasurementmodelandthedifferentwaystheUKFcanbeintegratedintotheBLOSradarsystem. 4.ChallengesinBLOSRadarSystems Inthissection,thechallengesencounteredinBLOSradarsystemsarediscussed.Thisincludesclutter,multipathpropagation,andhighmeasurementuncertainties.TheimpactofthesechallengesontargettrackingandthelimitationsoftheUKFalgorithminaddressingthemarehighlighted. 5.ImprovingUKFPerformance ThissectionproposesseveralenhancementstotheUKFalgorithmtoovercomethelimitationsdiscussedintheprevioussection.Theseinclude: a.Incorporatingcluttermodelingandfilteringtechniquesforimprovedtargetdetectioninclutteredenvironments. b.U