SC_FDE系统信道估计与频域均衡算法研究与仿真
单载频频域均衡的信道估计和频域均衡研究仿真20097287L0IDFT2.2.2CSICSI元(n),FFTCSIX(k),R(k)CS辅助数据信道捕获H(K)同步m)的TRA数据一跟踪CSI均衡F判决S重构X()FRC SIX1=(Xn…kXo=(Xn…NHo(k)=R(k)h=0,1,…;N-1(5)CSIUH re(le)Ul=2…,U-1;n=1,…,NCSI(7)(2)CSICSISG FDE率辅助数据块数据数据○ooo●○OOO●CP○oo●○●●0○o○●○o○○:(zero forcing, ZF)(m inimum mean square error, MMSE)ZEC(k)=;k=0,1,…,N-1(8)X(h)XHY= XH+ W=t wX(k)XuNH(b
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Two Dimensional Phase Unwrapping Theory Algorithms and Software
Two Dimensional Phase Unwrapping Theory Algorithms and Software，扫描文档，清晰度一般。GTWO-DIMENSIONALPHASE UNWRAPPINGTHEORY ALGORITHMSAND SOFTWAREDennis C. ghigliaSandia National LaboratoriesAlbuquerque, New MexMark D. PrittLockheed Martin CorporationGaithersburg, Maryland藏A WILEY-INTERSCIENCE PUBLICATIONJOHN WILEY SONS, INCNew York Chichester Weinheim Brisbane Singapore / Toronto2005060radar interferogram generated byDeathon each pass, The terrain elevations can be computed from thebut the phase differences must fig problem In regions of steeprrupted where there are radar shadow and "layover"effects. Surfaceoccurred between the two passes, which were 24 days apar alsopThis image was acquired as part of a program for the Terrain Modeling Project Officended byEngineering Center. The SAR data was provided by Radarsat Intenational THinterferogram was generated and provided by Vexcel Corporation, Boulder, Coloradop00This text is printed on acid-free paper.Copyright o 1998 by John Wiley Sons, Inc. All rights reservedNo part of this publicationreproduced, stored in a retrievalsystem or transmitted in any form or by any means, elechanical photocopying, recording, scanning or otherwise,xcept as permitted under Sections 107 or 1O% of the 1976of the Publisher or authorization through payment of theontates Copyright Act, without cither theppropriate per-copy fee to the Copyright Clearance Center, 222750-4744. Requests to the Publisher for permission show(978)ood Drive, Danvers, MA 01923, (978)750-8400, faxnc.. 605 Third A venue. New York, NY 10158-0012(212)850-6011fax(212)850-6008,E-Mail:PERMREQ@WILEY.COMTwo-dimensional phase unwrapping: theory, algorithms, andsoftware/Dennis C Ghiglia and Mark D Pritt.SBN0-471-24935-1(cloth: alk. paper)1. Synthetic aperture radar. 2. Signal processing--Mathematics3. Interferometry. I Pritt. Mark D. [L. Title621.367-dc2l97-3803410987654321;4TWO-DIMENSIONALPHASE UNWRAPPINGFOREWORDTwo-dimensional phase unwrapping is the type of problem that is typically thedomain of the mathematician. It is both complex and abstract However, phaseunwrapping is also the core technology that enables radar interferometryOver the past decade interferometry has changed the way that we use radardata. Radar data are now used for precise measurement of surface topography inclouded regions. Additionally, spaceborne radar systems have proved effectivefor measuring surface changes from earthquakes and volcanic eruptions. Theseapplications have created a new class of radar data users primarily involved inmapping and remote sensing applicationIn Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Softwarethe authors unlock the mystery of phase unwrapping in interferometric datarocessing. This text provides a clear, concise treatment of phase unwrappingthat cannot be found in any other source. It presents for the first time therelationship between theory and application. Its uniform treatment of thevarious phase unwrapping techniques makes it a valuable resource for anyengineer or scientist involved in processing or exploitation of interferometricexpect that radar interferometry will increase in importance over the comingdecade with the development of airborne and spaceborne sensor systemsdesigned to optimally exploit this tcchnology. Two- Dimensionsping: Theory, Algorithms, and Software is an important contribution to ourinderstanding of radar interferometry that will bencfit both research intoadvanced techniques and the design of these future sensor systemsJOHN C. CURLANDEPresident and CEOVexcel CorporationPREFACETwo-dimensional phase unwrapping arises most naturally in, but is notrestricted to, interferometric applications. Measured or calculated phasevalues from two or more mutually coherent multidimensional signals are relatedn a nonlinear manner to a desired physical quantity of interest. The nonlinearityis in the form of"wraps"or cycle discontinuities where an underlying two-dimensional phase is wrapped into the interval (T, r. The wrapped phasemust somehow be unwrapped in order to provide an estimate of the underlyingphysical quantity. Estimation of surface topography from interferometricsynthetic aperture radar(SAR)or extremely accurate profiling of mechanicaparts by optical interferometers are two such examplesOriginally developed for military reconnaissance, SAR is now experiencingnew life in civil applications. In fact civilian and commercial interests are rapidlbecoming the drivers of technology. Clever utilization of the coherent SArimagery in interferometric configurations makes possible the measurement ofsurface topography to accuracies much better than the spatial resolution( 0.3meters to several meters)of the SaR images themselves. Indeed, as is commonplace with interferometers, measurement sensitivities are on the order of theoperating wavelength, which is typically a few centimeters for SAR. Imaginggeometries, noise, and other operational factors degrade performance some-what from centimeter-scale accuracies, but nevertheless SAR interferometrymakes possible global topographic mapping in a timely fashion, in daylight or atnight, in all weather conditions, and with unprecedented accuracyinterferometry also can detect deformations of the earths crust on the orderof millimeters, a capability that shows promise for the timely detection ofearthquakes or volcanic eruptionsThese exciting possibilities have led to an explosive growth in the field of phaseunwrapping as indicated by the increasing number of journal publicationsNewcomers to SAR interferometry and related disciplines will eventuallyonfront the phase unwrapping problem and, undoubtedly, will encounter arather bewildering variety of ideas and algorithms, including those based onneural networks, simulated annealing, cellular automata, genetic algorithms,and other unusual constructs. Which of these are good? Which are not? We doThroughout this book we use the notation(-丌,丌 to represent the interval-丌
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