基于分?jǐn)?shù)階傅里葉變換的線性調(diào)頻信號估計與分離研究.pdf

1、聲明本學(xué)位論文是我在導(dǎo)師的指導(dǎo)下取得的研究成果，盡我所知，在本學(xué)位論文中，除了加以標(biāo)注和致謝的部分外，不包含其他人已經(jīng)發(fā)表或公布過的研究成果，也不包含我為獲得任何教育機構(gòu)的學(xué)位或?qū)W歷而使用過的材料。與我一同工作的同事對本學(xué)位論文做出的貢獻均已在論文中作了明確的說明。如11年弓月弓日學(xué)位論文使用授權(quán)聲明南京理工大學(xué)有權(quán)保存本學(xué)位論文的電子和紙質(zhì)文檔，可以借閱或上網(wǎng)公布本學(xué)位論文的部分或全部內(nèi)容，可以向有關(guān)部門或機構(gòu)送交并授權(quán)其保存、借閱或

2、上網(wǎng)公布本學(xué)位論文的部分或全部內(nèi)容。對于保密論文，按保密的有關(guān)規(guī)定和程序處理。研究生簽名：加11年弓月弓日Abstract基于分?jǐn)?shù)階傅里葉變換的線性調(diào)頻信號估計與分離研究AbstractLinearfrequencymodulation(LFM)signaliswidelyusedinradarandcomnmnicationsystemBecauseofthecomplicatedelectromagneticenvironment，

3、signalsortingandrecognitionbecomemoredifficultEspeciallyunderthelowsignaltOnoiseratio，LFMsignalparameterestimationhasgreatsignificanceMeanwhile，receivermayreceivemorethanonesignalsatonetime，SOhowtodetectandseparatesignal

4、sbecomeallimportantresearchtopicinthefieldofelectroniccountermeasureThemainresearchofthispaperishowtodetectandseparateLFMsignalsbyFractionalFourierTransform(FrFT)Thetraditionaltime—frequencyanalysismethodsuchasShortTimeF

5、ourierTransform(STFT)andWignerVilledistributionhaveproblemwithlowresolutionorcrossterminterferencewhileestimatingtheparameterofLFMsignalsComparedtOtraditionaltime—frequencyanalysismethodFrFTdoesnOthavetheseproblemsButtwo

6、dimensionalsearchisinvolvedinF汴TwhichhaveahugeamountofcomputationThiswillaffectrealtimeperformanceofsignaldetectionTwokindsofImprovedalgorithmarementionedinthispaper：OneisLFMsignalparmrxeterestimationbasedonFrFTinterpola

7、tionmethod；anotherisLFMsignalparameterestimationbasedonNuttallwindowEnergyBarycenterCorrectionMethod(EBCM)AlgorithmbasedOilFrFTInterpolationmethodusingspectruminterpolationtoenlargethesearchstepsizerandreducecomputationA

8、lgorithmbasedonNuttallwindowisusingthegoodperformanceofNuttallwindowtoimprovetheaccuracyofEBCM，andthen，estimatetheOrdernumberofFrFTbythecorrespondingrelationbetweenfrequencymodulationrateandtheOrdernumberofFrFTBythisOrde

9、rnumber，wecanhaveaccurateestimationoffrequencymodulationrateandinitialfrequencybysmallrangesearchAtlast，WeuseMATLABtosimulatethetwoAlgorithmMulti—componentsignalseparationmethodbasedonCLEANusingthemethodbymaskingknownsig

10、nalsThismethodcanseparatemulti—componentsignalsandcompletetheparametersestimationButthemethoddoesn’tfittotheideaofdimensionalityreductioninvolvedintwokindsofImprovedalgorithmPaperintroduceaimprovedmulti—componentsignalse

11、parationmethodbasedonCLEAN，whichcanbeusedintwokindsofImprovedalgorithmWealsouseMATLABtosimulatetheperformanceFinally，ahardwaresystemwithDSPisusedtotestthealgorithmTheexperimentalresultsareconsistentwiththeMATLABsimulatio