Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises, 4th Edition PDF
Preview Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises, 4th Edition
FFIRS 12/14/2011 9:6:46 Page2 FFIRS 12/14/2011 9:6:46 Page1 FOURTH EDITION Introduction to Random Signals and Applied Kalman Filtering WITH MATLAB EXERCISES FFIRS 12/14/2011 9:6:46 Page2 FFIRS 12/14/2011 9:6:46 Page3 FOURTH EDITION Introduction to Random Signals and Applied Kalman Filtering WITH MATLAB EXERCISES Robert Grover Brown ProfessorEmeritus IowaStateUniversity Patrick Y. C. Hwang RockwellCollins,Inc. John Wiley & Sons, Inc. FFIRS 12/14/2011 9:6:46 Page4 VPandPublisher DonFowley AssociatePublisher DanSayre EditorialAssistant CharlotteCerf SeniorMarketingManager ChristopherRuel SeniorProductionManager JanisSoo SeniorProductionEditor JoycePoh Designer JamesO’Shea Thisbookwassetin10/13PhotinaRegularbyThomsonDigital.PrintedandboundbyCourierWestford. ThecoverwasprintedbyCourierWestford. Thisbookisprintedonacidfreepaper. 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Evaluationcopiesareprovidedtoqualifiedacademicsandprofessionalsforreviewpurposesonly,forusein theircoursesduringthenextacademicyear.Thesecopiesarelicensedandmaynotbesoldortransferred toathirdparty.Uponcompletionofthereviewperiod,pleasereturntheevaluationcopytoWiley.Return instructions and a free of charge return shipping label are available at www.wiley.com/go/returnlabel. OutsideoftheUnitedStates,pleasecontactyourlocalrepresentative. LibraryofCongressCataloging-in-PublicationData Brown,RobertGrover. IntroductiontorandomsignalsandappliedKalmanfiltering:withMATLABexercises/RobertGrover Brown,PatrickY.C.Hwang.—4thed. p.cm. Includesindex. ISBN978-0-470-60969-9(hardback) 1. Signalprocessing—Dataprocessing. 2. Randomnoisetheory. 3. Kalmanfiltering—Data processing. 4. MATLAB. I. Hwang,PatrickY.C. II. Title. TK5102.9.B752012 0 621.3822—dc23 2011042847 PrintedintheUnitedStatesofAmerica 10 9 8 7 6 5 4 3 2 1 FPREF 12/14/2011 9:10:39 Page5 Preface To The Fourth Edition We are happy to report that Kalman filtering is alive and well after 50 years of existence. New applications keep appearing regularly which broadens the interest throughoutengineering.This,ofcourse,hasallbeenmadepossiblebythefantastic advancesincomputertechnologyoverthepastfewdecades.Ifitwerenotforthat, the neat recursive solution for the Wiener filter problem that R. E. Kalman introducedin1960wouldprobablyonlyberememberedasaninterestingacademic curiosity,inengineeringliteratureatleast.Enoughofthehistory;clearly,Kalman filteringisheretostay.Itiseminentlypractical,andithaswithstoodthetestoftime. ThistextisarevisionoftheThirdEditionofIntroductiontoRandomSignals andAppliedKalmanFilteringwithMATLABExercises.Kalmanfilteringhasnow reachedastageofmaturitywhereavarietyofextensionsandvariationsonthebasic theory have been introduced since the Third Edition was published in 1997. We haveincludedsomeofthesedevelopments,especiallythosethatdealwithnonlinear systems.TheextendedKalmanfilterisincludedbecauseitisusedwidelyanditis still the preferred solution to many integrated navigation systems today, just as it was a few decades ago. Ourintentisstilltokeepthebookattheintroductorylevelwithemphasison applications. We feel that this material is suitable for undergraduate as well as beginninggraduatecourses.Thenecessaryprerequisitematerialforthisbookwill befoundinanumberofbooksonlinearsystemsanalysisorlinearcontrolsystems. Wethinkthatwehaveimprovedtheorganizationofthetextmaterialinthisedition bymakingadistinctseparationoftherandomsignalsbackgroundmaterial(Part1) andthemainsubjectofappliedKalmanfiltering(Part2).Studentswhohavealready hadacourseinrandomprocessesandresponseoflinearsystemstorandominputs may want to move directly to Part 2 and simply use Part 1 as reference material. Part1(Chapters1through3)includestheessentialnotionsofprobability,an introduction to random signals and response to linear systems, state-space model- ing, and Monte Carlo simulation. We have found from teaching both university- creditandcontinuing-educationcoursesthatthemainimpedimenttolearningabout Kalman filtering is not the mathematics. Rather, it is the background material in randomprocessesthatusuallycausesthedifficulty.Thus,thebackgroundmaterial in Part 1 is most important. v FPREF 12/14/2011 9:10:39 Page6 vi PREFACETOTHEFOURTHEDITION Part 2 (Chapters 4 through 9) contains the main theme of the book, namely appliedKalmanfiltering.Thispartbeginswiththebasicfilterderivationusingthe minimum-mean-square-errorapproach.Thisisfollowedbyvariousembellishments onthebasictheorysuchastheinformationfilter,suboptimalanalysis,conditional density viewpoint, Bayesian estimation, relationship to least squares and other estimators,smoothing,andothermethodsofcopingwithnonlinearities.Chapter8 isacompletelynewchapterthatexpandsonthecomplementaryfiltermaterialinthe Third Edition. Chapter 9 deals entirely with applications, mainly those in the engineering field of positioning, navigation, and timing (PNT). The authors wish to thank all of our former students and colleagues for their manyhelpfulcommentsandsuggestionsovertheyears.Specialthanksgoestothe late Larry Levy. His generous counsel and advice on many aspects of Kalman filtering will certainly be missed. RobertGroverBrown Patrick Y. C. Hwang FTOC 12/14/2011 9:44:19 Page7 Brief Contents Preface v PART 1 RANDOM SIGNALS BACKGROUND 1 1 ProbabilityandRandomVariables:AReview 3 2 MathematicalDescriptionofRandomSignals 57 3 LinearSystemsResponse,State-SpaceModeling,and MonteCarloSimulation 105 PART 2 KALMAN FILTERING AND APPLICATIONS 139 4 DiscreteKalmanFilterBasics 141 5 IntermediateTopicsonKalmanFiltering 173 6 SmoothingandFurtherIntermediateTopics 207 7 Linearization,NonlinearFiltering,andSampling BayesianFilters 249 8 The“Go-Free”Concept,ComplementaryFilter,and AidedInertialExamples 284 vii FTOC 12/14/2011 9:44:19 Page8 viii BRIEFCONTENTS 9 KalmanFilterApplicationstotheGPSandOther NavigationSystems 318 A APPENDIX LaplaceandFourierTransforms 365 B APPENDIX TheContinuousKalmanFilter 371 Index 379
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