分数域信号与信息处理及其应用 (9).pdf
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1、158IEEE TRANSACTIONS ON SIGNAL PROCESSING,VOL.56,NO.1,JANUARY 2008Sampling and Sampling Rate Conversionof Band Limited Signals in the FractionalFourier Transform DomainRan Tao,Senior Member,IEEE,Bing Deng,Wei-Qiang Zhang,Student Member,IEEE,and Yue WangAbstractThefractional Fourier transform(FRFT)ha
2、s becomea very active area in signal processing community in recent years,with many applications in radar,communication,information se-curity,etc.,This study carefully investigates the sampling of a con-tinuous-timebandlimitedsignaltoobtainitsdiscrete-timeversion,as well as sampling rate conversion,
3、for the FRFT.Firstly,basedon product theorem for the FRFT,the sampling theorems and re-construction formulas are derived,which explain how to sample acontinuous-time signal to obtain its discrete-time version for bandlimited signals in the fractional Fourier domain.Secondly,the for-mulas and signifi
4、cance of decimation and interpolation are studiedin the fractional Fourier domain.Using the results,the samplingrate conversion theory for the FRFT with a rational fraction asconversion factor is deduced,which illustrates how to sample thediscrete-time version without aliasing.The theorems proposed
5、inthis study are the generalizations of the conventional versions forthe Fourier transform.Finally,the theory introduced in this paperis validated by simulations.Index TermsFractional Fourier transform(FRFT),samplingrate conversion,sampling theorem.NOMENCLATUREFTFourier transformFRFTFractional Fouri
6、er transform.DTFRFTDiscrete-time FRFT.Notation for the FRFT.Transform result offor the FRFT.Notation for the DTFRFT.Transform result offor the DTFRFT.I.INTRODUCTIONTHE fractional Fourier transform(FRFT)has a historydating back to the 1930s 1.It was then employed byNamias to solve some differential a
7、nd partial differentialManuscript received May 20,2006;revised April 27,2007.The associateeditor coordinating the review of this manuscript and approving it for publi-cation was Dr.Antonia Papandreou-Suppappola.This work was supported inpart by the National Science Foundation of China under Grants 6
8、0232010 and60572094,and in part by the National Science Foundation of China for Distin-guished Young Scholars under Grant 60625104.R.Tao and Y.Wang are with the Department of Electronic Engineering,Bei-jing Institute of Technology,Beijing 100081,China(e-mail:).B.Deng is with the Department of Electr
9、onic Engineering,Beijing Insti-tute of Technology,Beijing 100081,China,and also with the Department ofElectronic Engineering,Naval Aeronautical Engineering Institute,Yantai City264001,China(e-mail:navy_).W.-Q.Zhang is with the Department of Electronic Engineering,TsinghuaUniversity,Beijing 100084,Ch
10、ina(e-mail:).Digital Object Identifier 10.1109/TSP.2007.901666equations in quantum mechanics from classical quadraticHamiltonians 2.The results were later improved by McBrideand Kerr 3.They developed operational calculus to definethe FRFT.The FRFT is a generalization of the conventionalFouriertransf
11、orm(FT)with potential applications.But,withoutproper physical illumination and fast digital computation algo-rithm,the methodology had remained unknown to the signalprocessing community until the introduction of the efficientdigital computational algorithms of the FRFT and the inter-pretation as rot
12、ation in the time-frequency plane 410.TheFRFT processes signals in a unified time-frequency domain.Comparing with the FT,the FRFT is more flexible and suitablefor processing nonstationary signals due to an additional degreeof freedom.Furthermore,the fast algorithm of the discreteFRFT has also been p
13、roposed.Therefore,the FRFT has beenwidely applied in radar,communication,information security,etc.518.The FRFT of theorder can be interpreted as a rotation inthe time-frequency plane with an angle,and the time domainand frequencydomain arethe specialcasesof theFRFTdomainwithbeingand,respectively,whe
14、reis aninteger 4.Hence,the conventional Shannon sampling theoremfor the FT can also be considered as a special case of the sam-plingtheoremfortheFRFT1923.Basedontherelationshipbetween the FT and FRFT,i.e.,the three decomposition stepsof the FRFT 4,Xia 19,Zayed 20 and Erseghe et al.21,independently g
15、eneralized the classical Shannon theorem fromthe frequency domain to the FRFT domain.Based on chirp-pe-riodicity Erseghe generalized the FT for continuous-time,peri-odic continuous-time,discrete-time,periodic discrete-time sig-nals to four corresponding versions of the FRFT 21.In 22,Shannonsinterpol
16、ation theorem was generalizedfor the FRFT.It was concluded that a signal limited in a certain FRFT domaincan be represented by its samples in any other FRFT domain.In23,Zayedderivedtwosamplingformulastoreconstructabandlimited or time limited signal,which use samples from both thesignalanditsHilbertt
17、ransformationsampledathalftheNyquistrate.Since signals are always processed within a finite timeinterval and a finite bandwidth in practical engineering appli-cations,signal sampling based on the conventional Shannonsampling theorem can meet the criteria of ideal reconstruction.However,the sampling
18、theorem for the FRFT shows that thesampling method is not always efficient with the possibility ofunnecessary computational cost.In other words,a signal canpotentially be sampled with a rate less than the Nyquist ratewithout aliasing of signals FRFT.1053-587X/$25.00 2007 IEEETAO et al.:SAMPLING AND
19、SAMPLING RATE CONVERSION OF BAND LIMITED SIGNALS159The sampling theorems mentioned earlier explain how tosample a band limited signal without aliasing.The advances indigital signal processing necessitates performing more complexsignal processing operations such as coding,transmitting andstoring.In o
20、rder to reduce the computational load as wellas saving the storage space,different sampling rates and theconversion between them are typically required in a signalprocessing system.Under these circumstances,the theoryof multirate signal processing was introduced and improved24.This theory explains h
21、ow to implement the samplingrate conversion from a discrete-time signal to another.Theconventional sampling rate conversion theorem is operatedin the FT domain,which helps to eliminate spectral aliasingdue to decimation and mirror because of interpolation.If asignal is sampled by using the sampling
22、theorem for the FRFT,the conventional sampling rate conversion theorem can notguarantee undistorted sampling rate conversion.Therefore,several questions are raised,such as 1)how to generalize theconventional sampling rate conversion theorem?and 2)how toachieve undistorted sampling rate conversion by
23、 eliminatingthe influences on signals FRFT caused by interpolation anddecimation?In this paper,the sampling theorem for band limited signalsin the FRFT domain is deduced from the viewpoint of signalsand systems.Then,some discussions are presented to demon-strate its implementation.Next,we propose th
24、e generalizationof conventionalsamplingrateconversion theorem,i.e.,thesam-pling rate conversion theorem with a factor of rational fractionfortheFRFT.Afterthat,simulationsarepresented.Finally,con-clusions are given.II.PRELIMINARIESThe continuous-time FRFT with angleof a signalisdefined as 4(1)wherein
25、dicatestherotationangleinthetime-frequencyplane,isthekernelfunction,shownin(2)atthebottomofthepage,where.The discrete-time FRFT(DTFRFT)is defined as 21(3)Its inverse is(4)whereis the sampling period,denotes the integral in-terval with the width.The FRFT has the following four special cases:(5)(6)(7)
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