策略为王源代码(for VS2015)

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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雷达信号处理程序，包括线性调频,匹配滤波，产生目标回波加噪声,回波积累，时域脉压，频域脉压,加窗脉压，相干积累，mti对消，mtd检测，cfar检测,欢迎下载

adaboost 演示demo（基于Matlab，学习算法包括决策树、神经网络、线性回归、在线贝叶斯分类器等），动态GUI显示学习过程、vote过程等

介绍了NCO 数字控制振荡器的工作原理 详细分析了数控振荡器的性能指标和其在FPGA中的实现方法 最后给出了新设计的数控振荡器在QUARTUS2 中的仿真结果第12卷第11期电子元器件用VoL 12 No. 112010年11月Electronic Component Device ApplicationsNov.20102069n80#顶(101#围100am)20020数篇0291潮0x)萨:日6959173国0国L图1 QUARTUS II下仿真波形图功率谱密度函数信号波形图X:4080-sn(2pi*18e61)Y5014余强信号H正弦信"7彐300>…-÷a是2500300035004C004500500055006000250255260265270275280285290图2输出频率为408ⅥH的信号波形与功率谱密度5结束语参考文献本文通过分析数控振荡器的实现原理和性张欣扩频通信数字基带信号处理算法及其vS实现能,给出了通过FPGA来实现NCO的具体方法[M]北京:科学出版社,2004同时通过 QUARTUSⅡ中的仿真验证了本设计的[2]楼顺天MAT.AB7x程序设计语言[M西安:西安电子科技大学出版社,200正确性。结果证明,用该方法设计的NCO可以输3]汤伟良,等数控振荡器在FPGA中的实现门微型机与出多种频率的信号,同时也可以减少资源消耗。应用,2003,22)X(上接第41页表1分档信息及对应放大/哀减量息,也提高了实时数控AGC电路的动态范围和整档位输入信号功放大衰档位输入信号功放大衰个系统的精度。实验结果表明,该电路能够实现号率范围/dBm减量dB号率范围/dBm诚量/dB实时AGC的电路功能,并有效扩展了动态范围。1「12,20186「-33,-24)3523,12)7参考文献36,3)8[51,4杨小牛,楼才义,徐建良软件无线电原理与应用[Ml4-15,-6)9[-80,-51)北京:电子工业出版社,200151-24,-1526实时放大衰减。同时利用FPGA器件良好的数字2]韩尧秦开宇基于数字补偿的实时自动增益控制技术研究[.电子科技大学学报,2007,36(1):79-81特性实现了数控AGC的设计,从而实现了对信号3陈爽高性能频谱分析仪中频信号处理技术研究U的实时数字增益补偿,有效减少了电路体积。同合肥:合肥工业大学,2007时,采用两级数控增益放大/衰減器级联和根据[4曹鹏,费元春.大动态范囯数字中频ACC系统的设计两路不同增益通道提取的度值来判断档位信门北京理工大学学报,2003,23(5:613-61644电子元器件在用2010.11www.ecda.cn

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morlet小波分析matlab程序，用于气象数据统计与分析

matlab绘制温度分布场，通过传感器矩阵采集环境变量之后，通过matlab中的二维样条插值法，获取庞大的计算值，来构建温度分布场

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c# MODBUS协议 上位机.htm软件的基本结构：采用定时器（Timer控件）为时间片。串口采用serialPort1_DataReceived中断接收，并进行MODBUS格式判断。把正确接收的数据取出，转换为有特定的结构体中。数据通过时间片实时刷新。