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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船舶动力定位参数辨识
对船舶数学模型的各个推进器参数进行系统辨识，具有实际价值李文华,等:船舶动力定位系统数学模型参数辨识方法研究针对动力定位技术的发展,我国研究人员也进表1离散时间摘要扩展卡尔曼滤波行了积极有益的探索。文献[]用固定增益的卡尔f(k+1)=F((k),(k)+vw(k)曼滤波估计低频运动,而高频运动则用一个参数模系统模型量测|/(k)~N(O,Q(k》)x(k)=H((k)();型来模拟,并用递推增广最小二乘法来估计参数,从u(k)-N(0,Q(k)而估计出船舶的髙频运动。通过控制计算和模拟试初始情况1(0)+5np(0)=验取得了良好的效果。文献[12]提出了水面舰船动力定位控制系统模型参数的离线最速下降寻优的状态估计传递|(k+1)=F((k),()误差协方差传递辨识方法,提高了动力定位系统研制过程的工作效P(h+1)=(h)P()(k)+r(kQ(k )r(k)率。文献[13]在建立船舶三维几何模型基础上,对K()=P(k)HT(k)H()(kH()+R()]-满载船舶从浅水40m到深水500m的水动力系状态估计更新)=()1)((数进行数值计算。利用三维线性势流理论在频域误差协方差更新P)=kk)H(FLK)H()y里研究船舶在浅水中的辐射问题,应用三维源汇分K()R(k)K(k)布法对不同水深下船舶运动的水动力系数,包括附定义φ(k)=0()JH(-)加质量和阻尼系数进行数值计算与分析,得出了有(k)H(k)=0(k)限深水域的附加质量和阻尼系数的渐进特性。文献14]考虑具有修正PM波谱的长峰不规则浪,基于尾部隧道式侧推m,艏部隧道式侧推,艄部方海浪幅值响应算子(RAO研究了船舶在海浪中的六角式推进器。质量阵M可利用文献9]里介绍自由度运动预报模型。为了有效地量化海洋环境对的 Strip Theory计算得到:动力定位船舶的作用,文献[5提出了海洋环境负从/1127400018902-00744载(包括风、海浪和海流)的建模方法,并运用00.07440.1278MATLAB的M文件和SIMUⅠNK分别编制了风干为了得到需要辨识的量需重复进行3项(每项扰力和力矩计算及随机海浪的仿真程序。在三级海2次,共6次)海上试验,以此提高参数估计器的收况下,实现了对海洋环境的仿真,得到了合理的仿真敛性和表现。具体如下结果。文献[1]考虑到船舶的动态特性存在固有的第1项:解耦了的纵荡运动。船舶仅依靠主螺强非线性以及非线性控制改善系统性能和鲁棒性的旋桨山和实现恒速前进,艏向通过艏侧推控制。能力,将非线性控制理论应用到船舶动力定位控制第2项:结耦了的横荡与艏摇运动。通过三个隧道系统的设计中,对某供应船的计算机模型进行仿真,式推进器砌、4、实现两次结耦了的横荡与艏摇运验证了非线性控制系统是有效的。文献[17]提出并动。第3项:在结耦的横荡与艏摇运动中得到方位验证了基于线性核函数在线支持向量回归的模型预角式推进器u的推力系数K6测控制方案。在线支持向量回归算法的引入可以通第1项是为了计算主螺旋桨的推力系数K1和过在线调整,确保预测模型的精确性。Xa,需要的输入量是X本文中X的计算方法是利22船舶数学模型参数辨识用文献[19]里介绍的切片法。第2项是为了计算结文献[18]讨论了使用两个并行测量序列来估计耦了的横荡与艏摇运动的参数数值,可以辨识出的动力定位船舶模型参数的离线并行扩展卡尔曼滤波向量为[ YYNNK3K5]第3项是为了计算全方器算法(O- line parallel extended Kalman filter位推进器的推力系数K6( EKF) Algorithm),见表1。最后采用一项以供给船使用动量方程来代替标准动力学方程,不仅可为对象的全尺度的海上试验来验证提出的参数估计以显著提高状态和参数估计器的性能还具有以下器的收敛性和鲁棒性。优点:实验对象以挪威ABB公司的“ Far Scandia”号供(1)增加数据冗余度;给船为原型。该船总长762m,船宽18:8m,型深(2)降低量测噪声;825m,吃水625m,净吨位4200t,主发动机功率(3)降低环境干扰;3533kW。推进器配置左右舷两个主推进器u1、l2,(4)增加数据记录长度第23卷第3期(总第135期)船羔vd.23N.3012年6月shiP boatJune, 2012(5)以对参数分批进行辨识等手段提高参数辨风。将风速分量定义为识的精确度。L=v,cos(ψ图2显示了实验辨识得到的A和。其中A包(5)W V sin(B-0)含的待求未知量[XyYM而R包含的待求末式中和v分别为风速在X轴和Y轴的分量;v知量是[kk2k3k4k5k6]。和月分别表示风速和风向。如图1所示。假设风速远大于船速,风在纵荡、横荡和艏摇方向的负荷向量可表述为As elements.pAcM(o)V, IV0.5p.A_C-(r )V,V6)0.SpA,Lo C(rm)VV.式中,风的相对角为y=ψp为空气密度,单位e号为kgm3;Lm为船舶总长,单位为m;V为相对风速,103K elements单位为kn;A-和A为正投影面积和侧投影面积,2015单位均为m2;C(y)Cn(y)和C(4)分别为纵荡横荡和艄摇方向的无因次风系数,是通过 Isherwood半经验公式得到的。00003,波浪扰动数学模型波浪干扰力一般分为两种:一种是一阶波浪干图2实验辨识得到的参数曲线扰力,也称高频波浪干扰力。这是在假设波浪为微幅波,未引起船舶大幅摇荡的情况下,认为船舶受到经实验辨识出的动量方程中的量:与波高成线性关系并且与波浪同频率的波浪力。另0.03180种是二阶波浪力,也称波浪漂移力该波浪力与波A000602006l8高平方成比例。0.0075_0.2454这种具有高频率小振幅振荡特性的波浪所产生K=103ding([93,93,20,2.0,28,26]的一阶波浪干扰力最主要是引发船舶的纵摇和垂荡经过计算公式D-M得到运动,对横摇的影响稍次之,而对横荡及艄摇运动的002820影响相对来说就小一些。至于具有慢时变特性的二00.0130475900.081419676阶波浪干扰力,本身同时又是非线性的,它仍然和波写成动力定位模式下的状态空间表达式为:浪的频率有关。波浪的二阶漂移力不但会改变船舶元=AU+Bx(4)疔的航向和航迹,尤其对于在锚泊状态下船舶位置的移动及钻井平台的动力定位系统的工作等均有式中A=MA4M,并且B=MTK。其数值表达式为:重要影响00318000.062800030下面介绍一种估算二阶波浪漂移力方法。19740.0046-0.2428年, Newman提出一种应用频域波浪漂移力系数的0008200082000估算方法。通过把波谱(通常选用PM谱)分为N0∞505-069000108等份,每份有相对应的波浪频率m和波幅A。这样波浪漂移力对横荡、纵荡、艏摇运动的作用力计算公3环境扰动数学模型式为131风扰动数学模型A,(T(W,B=-y)1(W+)风的作用可分为平缓变化的风和快速变化的李文华,等:船舶动力定位系统数学模型参数辨识方法研究[5] Fossen T L. Handbook of Marine Craft Hydrodynamics and式中,T()x0是频域波浪偏移力公式fB是平均Motion Control[M]. Wiley Sons Ltd, 2011: 81-83.波浪方向:是随机的相角。[6] Balchen J G, Jenssen N A, Saelid S Dynamic Positioning可以通过对本估算式进行改变,以避免在数值Using Kalman Filtering and Optimal Control Theory[C]/上产生无物理意义的高频分量。还可对本式进行扩Proceedings of IFAC/IFIP Symposium on Automation in展,用来包括波浪蔓延( wave spreading)。Offshore Oil Field Operation Norway 1976: 183-18633海流扰动数学模型[7]Balchen J G, Jenssen N A Mathisen E, et al. Dynamic作用在海上动力定位船舶上的海流具有方向和Positioning System Based on Kalman Filtering and OptimalControl[J]Modeling, Identification and ControL 1980, 1(3)速度的特征,研究中一般不考虑在大地坐标系下铅135-163垂方向运动。海流分为恒定流和潮汐流。恒定流一般[8] Strand JP, Fossen t inonlinear Passive Observer Design为固定方向和速度的海流,如洋流。潮汐流指海洋for Ships with Adaptive Wave Filtering, In: New Directions因为潮汐运动而引起的海水流动,其典型的表现为in Nonlinear Observer Design(Nijmeijer H, Fossen T L)海流方向的缓慢变化。但对于动力定位来说,海流[M].London: Springer-Verlag London Ld, 1999: 113-134的大小与方向可以认为是确定的,所以海流的模型[9] Guttorm t, Jerome J, Fosset I. Nonlinear Dynamic可以统一按照大小和方向恒定来确立。流的速度分Positioning of Ships with Gain-Scheduled Wave Filtering量表示为5:[C]//The Proceedings of 43rd IEEE Conference orL=V2cos(ψ)Decision and Control, Atlantis, Paradise Island, BahamasDecemher2004:5340-5347ve=y sin(8-n)式中:和v分别为流速在X轴和y轴的分量;V10 i Do K d. Global Robust and Adaptive Output FeedbackDynamic Positioning of Surface Ships[C]/The Proceedings和月分别代表流速和流向。如图1所示。of 2007 IEEE Internati在此没有考虑第摇方向的流速,而海流对水面Automation. Roma, April 2007: 10-14船舶的作用可以通过将各海流速度分量引人到船的1]王晓声船舶动力定位系统设计及试验研究门J国造运动方程中由相对速度向量v=[u-,-a,r丁体现。船,1991(3):12-21[12]边信黔,严渐平,施小成船舶动力定位系统参数辨识4结论方法的研究[J]船舶工程,19994):36-38[13]姜哲,石珦,王磊动力定位船舶水动力参数数值试验本文讨论了船舶及推进器动力学数学模型与船研究[门]实验室研究与搡索,2005(12):14-17.舶外界环境干扰因素数学模型的建模策略。通过对14]李文魁张博田蔚风等.一种波浪中的船舶动力定位已有研究方法的分析研究与总结,有助于建立适用运动建模方法研究[]仪器仪表学报,2007(6):1051于各种海况和操作模式的船舶动力定位系统非线性数学模型。[15]施小成王元慧船舶动力定位海洋环境的建模与仿真J,计算机仿真,2006(11):237-239[16]刘芙蓉陈辉基于非线性控制理论的船舶动力定位控[参考文献制系统的数学模型[〕船海工程,209(5):92-95[1]杜佳璐,张显库汪思源,等船舶动力定位系统的自适[17]邓志良,胡寿松,张军峰船舶动力定位系统的在线模应非线性控制器设计[ C]/proceedings of the2 g chinese型预测控制[门中国造船,2009(6):879Control Conference. Beijing, 2010: 585-589.[2]周利,王磊,陈恒动力定位控制系统研究[船海[18] Fossen T I.Identification of Dynamically Positioned Shipe[].Control Engineering Practice, Volume 4, Issue 3, March程,008,37(2)86-911996:369-376[3]马超庄亚锋陈俊英船舶动力定位系统技术[J中国[19] FaltinsenO M Sea Loads on Ships and Oishore Structures造船,2009,50(增刊):52-57[4]贾欣乐,杨盐生船舶运动数学模型机理建模与数学建[M].Cambridge University Press, 1990:41-45模[M]大连大连海事大学出版社,199:294-356船舶动力定位系统数学模型参数辨识方法研究旧WANFANG DATA文献链接作者:李文华,杜佳璐,张银东,宋健,孙玉清,陈海泉, LI Wen-hua, DU Jia-luZHANG Yin-dong, SONG Jian, SUN Yu-ging, CHEN Hai-quan作者单位李文华,张银东,宋健,孙玉清,陈海泉, LI Wen-hua, ZHANG Yin-dong, SONG Jian, suN Yu-qing, chen Hai-quan(大连海事大学轮机工程学院大连116026),杜佳璐, DU Jia-lu(大连海事大学信息科学技术学院大连116026)刊名:船舶英文刊名:Ship boat年,卷(期):2012,23(3)参考文献(19条1. Balchen J G; Jenssen N A; Mathisen E Dynamic Positioning System Based on Kalmon Filtering andOptimal Control 1980(03)2. Balchen J G; Jenssen N A; Saelid S Dynamic Positioning Using Kalman Filtering and Optimal ControlTheory 19763. Fossen T I Handbook of Marine Craft Hydrodynamics and Motion Control 20114贾欣乐;杨盐生船舶运动数学模型机理建模与数学建模19995.马超;庄亚锋;陈俊英船舶动力定位系统技术2009(增刊)6.周利;王磊;陈恒动力定位控制系统研究[期刊论文]船海工程2008(02)7. Faltinsen 0 M Sea Loads on Ships and Offshore Structures 19908. Fossen t I Identification of Dynamically Positioned Ships 19969.邓志良;胡寿松;张军峰船舶动力定位系统的在线模型预测控制2009(06)10.刘芙蓉;陈辉基于非线性控制理论的船舶动力定位控制系统的数学模型[期刊论文]船海工程2009(05)11.施小成;王元慧船舶动力定位海洋环境的建模与仿真[期刊论文]计算机仿真2006(11)12.李文魁;张博;田蔚风一种波浪中的船舶动力定位运动建模方法硏究[期刊论文]仪器仪表学报2007(06)13.姜哲;石珣;王磊动力定位船舶水动力参数数值试验硏究[期刊论文]实验室硏究与探索2005(12)14.边信黔;严浙平;施小成船舶动力定位系统参数辨识方法的硏究[期刊论文]船舶工程1999(01)15.王晓声船舶动力定位系统设计及试验研究1991(03)Do K d Global robust and Adaptive Output Feedback Dynamic Positioning of Surface Ships 200717. Guttorm T; Jer(o)me J; Fossen T I Nonlinear Dynamic Positioning of Ships with Gain-Scheduled WaveFiltering 200418. Strand J P; Fossen T I Nonlinear Passive Observer Design for Ships with Adaptive Wave Filtering19.杜佳璐;张显库;汪思源船舶动力定位系统的自适应非线性控制器设计2010本文链接http://d.g.wanfangdata.comcn/periodiCalcb201203011.aspx
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