无源单站定位技术研究

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1、西南交通大学硕士学位论文无源单站定位技术研究姓名：李秀英申请学位级别：硕士专业：通信与信息系统指导教师：彭代渊20080501AbstractPassivelocalizationandtrackingsystemplaysanimportantroleintheelectronicreconnaissance，asitworkssilentlywithoutelectromagneticradiationandcoveringlargerregion．Singleobserverpassivelocalzaitionandtrackingsystemavoidtimesynchro

2、nizationanddatafusion，SOitattractsmoreandmoreresearchfoCUS．Essentially,passivelocalizationandtrackingtechnologyconsistsoflocalizationandtrackingmethodsandalgorithms．Theyarethetwokeypointsofpassivelocalizationtechnology，whichdecidetheprecisionandrapidity．Thus，thedissertationdoesdeeperresearcheso

3、nthetwoaspects．Thedissertationintroducesthemodeloftwo．dimensionalsingle·observerpassivelocationusmgbearinganditschangingrateinformation．Specially，thedissertationdoesdeeperresearchesonsomefilteringestimationalgorithm．．Firstly,backgroundofsingleobserverpassivelocalizationisintroduce·Astheobservab

4、ilityandmodeldevelopmentarethefundamentalproblem，theyarediscussedindissertation．Foliowly,someconsiderableestimationalgorithmsoflocalizationandtrackingarepresented．EKFalgorithmsisthemostclassicalnonlinearmethod，successfullyapplyinginmanypassivelocalizationproblems．Thecomputersimulationsarecarrie

5、doutandtheperformanceinpracticalapplicationisanalyzed．Followly，inordertoavoidtheweaknessofEKF,UKFalgorithminpassivelocalizationisstudieddeeply．UKFuseasetofassuredparticlestoestimatetheposteriorsprobability,haveagoodproperty111thepassivelocalizationandtrackingproblems．whereafter,particlefilterin

6、gisstudiedandappliedinpassivelocalizationsystem．Ituseasetofrandomsamples(alsocalledparticles)toestimatetheposteriorsprobability，haveagoodpropertyinthepassivelocalizationandtrackingproblems．Particlefilteringalgorithminordertoresolvedegeneracyofparticlefreque-ntlycarryoutresampling．Butresamplingo

7、fclassicalparticlefilteringalgorithmleadsampleimpoverishmentofparticle．ThereforedescribegeneticparticlefilteraIgorithm(GPFA)indissertation，indicateadvancedresamplingmethod，resolve西南交通大学硕士研究生学位论文第1Il页problemofsampleimpoverishmentKe