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1、PRINCIPLESOFRADARTARGETTRACKINGStephenChan,BrianDai,AdamLloyd,JonathanMacMillan,AlexanderMorrison,JoshuaNewman,MichaelSobinAdvisor:Mr.RandyHeuerAssistant:ZacharyVogelABSTRACTTrackingtargetswithradarisanimportantstepinensuringsafetyinsuchendeavorsasairtravelormilitaryoperations.Toaccoun
2、tforinherentinaccuraciesinrawradarmeasurementsofposition,andtoobtainaccuratevelocitydata,weimplementedanalgorithmcalledtheKalmanFilter.Theresultingtrackdatawasused,inconjunctionwithalgebraicandtrigonometricmethods,tosimulatetargetinterceptionandcollisionprevention.Oursystemledaninterce
3、ptoraircrafttoitstargetandwarnedpilotsofapotentialcollision,provingtheeffectivenessofourfilter.INTRODUCTIONGoalsofRadarTrackingRadarisatoolwhichmeasuresthepositionoftargets.Radartrackingusestheinformationfromtheradarsystemalongwithanappropriatealgorithmtodeterminethetrackofatarget.Usin
4、gtheinformationgeneratedbytheradarsystemandthealgorithm,theradartrackingsystemcanbeusedformoresophisticatedtaskssuchassendinganinterceptoratanymovingtargetaswellaspredictingandpreventingacollisionbetweentwotargets.ComplicationsfromRadarMeasurementAradarsystemaloneisinsufficientfortrack
5、ingtargets.Radarcanonlymeasurethepositionofanobject,notitsvelocity.Thereisalsonoisefoundinallradarmeasurementsthatleadstoerrorincollecteddata.Thisnoisecomesintwoforms,statenoiseandmeasurementnoise.Statenoiseoccursasaresultofchangesthataffectthetarget’spositionandvelocity,orstate,suchas
6、pilotcontrolinputsandweatherconditions.Themeasurementnoiseisinherentinallradarsystemsandoccurswhennoisegeneratedbythedeviceorexternalsourcesinterfereswiththemeasurement[1].KALMANFILTERTheKalmanfilter[1]isanefficientalgorithmforestimatingthestateofaprocessthatvarieswithtimeandhasinheren
7、tGaussiannoise.Itisanappropriatechoiceforthetrackingproblemforseveralreasons;itiscomputationallysimple,estimatestheerrorinitspredictions,copeswithmeasurementstakenatinconsistenttimeintervals,andcanbeextendedtotrackmanytargetssimultaneously.[5-1]Thisalgorithmwasdevelopedintheearly1960
