Table Of Content

Statistical and Adaptive Signal Processing Recent Titles in the Artech House Signal Processing Library Computer Speech Technology, Robert D. Rodman Digital Signal Processing and Statistical Classification, George J. Miao and Mark A. Clements Handbook of Neural Networks for Speech Processing, Shigeru Katagiri, editor Hilbert Transforms in Signal Processing, Stefan L. Hahn Phase and Phase-Difference Modulation in Digital Communications, Yuri Okunev Signal Processing Fundamentals and Applications for Communications and Sensing Systems, John Minkoff Signals, Oscillations, and Waves: A Modern Approach, David Vakman Statistical Signal Characterization, Herbert L. Hirsch Statistical Signal Characterization Algorithms and Analysis Programs,Herbert L. Hirsch Voice Recognition,Richard L. Klevans and Robert D. Rodman For further information on these and other Artech House titles, including previously considered out-of-print books now available through our In-Print-Forever®(IPF®) program, contact: Artech House Artech House 685 Canton Street 46 Gillingham Street Norwood, MA 02062 London SW1V 1AH UK Phone: 781-769-9750 Phone: +44 (0)20 7596-8750 Fax: 781-769-6334 Fax: +44 (0)20 7630-0166 e-mail: [email protected] e-mail: [email protected] Find us on the World Wide Web at: www.artechhouse.com Statistical and Adaptive Signal Processing Spectral Estimation, Signal Modeling, Adaptive Filtering, and Array Processing Dimitris G. Manolakis Massachusetts Institute of Technology Lincoln Laboratory Vinay K. Ingle Northeastern University Stephen M. Kogon Massachusetts Institute of Technology Lincoln Laboratory artechhouse.com Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the U.S. Library of Congress. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. This is a reissue of a McGraw-Hill book. Cover design by Igor Valdman © 2005 ARTECH HOUSE, INC. 685 Canton Street Norwood, MA 02062 All rights reserved. Printed and bound in the United States of America. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. All terms mentioned in this book that are known to be trademarks or service marks have been appropriately capitalized. Artech House cannot attest to the accuracy of this information. Use of a term in this book should not be regarded as affecting the validity of any trademark or service mark. International Standard Book Number: 1-58053-610-7 10 9 8 7 6 5 4 3 2 1 To my beloved wife, Anna, and to the loving memory of my father, Gregory. DGM To my beloved wife, Usha, and adoring daughters, Natasha and Trupti. VKI To my wife and best friend, Lorna, and my children, Gabrielle and Matthias. SMK ABOUT THE AUTHORS DIMITRISG.MANOLAKIS,anativeofGreece,receivedhiseducation(B.S.inphysics andPh.D.inelectricalengineering)fromtheUniversityofAthens,Greece.Heiscurrently amemberofthetechnicalstaffatMITLincolnLaboratory,inLexington,Massachusetts. Previously,hewasaPrincipalMember,ResearchStaff,atRiversideResearchInstitute.Dr. ManolakishastaughtattheUniversityofAthens,NortheasternUniversity,BostonCollege, and Worcester Polytechnic Institute; and he is coauthor of the textbook Digital Signal Processing: Principles, Algorithms, and Applications (Prentice-Hall, 1996, 3d ed.). His research experience and interests include the areas of digital signal processing, adaptive filtering, array processing, pattern recognition, and radar systems. VINAY K. INGLE is Associate Professor of Electrical and Computer Engineering at NortheasternUniversity.HereceivedhisPh.D.ineletricalandcomputerengineeringfrom RensselaerPolytechnicInstitutein1981.Hehasbroadresearchexperienceandhastaught courses on topics including signal and image processing, stochastic processes, and estimationtheory.ProfessorIngleiscoauthorofthetextbooksDSPLaboratoryUsingthe ADSP-2101 Microprocessor (Prentice-Hall, 1991) and DSP Using Matlab (PWS Publishing Co., Boston, 1996). STEPHENM.KOGONreceivedthePh.D.degreeinelectricalengineeringfromGeorgia Institute of Technology. He is currently a member of the technical staff at MIT Lincoln LaboratoryinLexington,Massachusetts.Previously,hehasbeenassociatedwithRaytheon Co.,BostonCollege,andGeorgiaTechResearchInstitute.Hisresearchinterestsareinthe areasofadaptiveprocessing,arraysignalprocessing,radar,andstatisticalsignalmodeling. e56toc.qxd 3/16/05 11:56 AM Page x CONTENTS Preface xvii 2.3 Discrete-Time Systems 47 2.3.1 Analysis of Linear, 1 Introduction 1 Time-Invariant Systems / 2.3.2 Response to Periodic Inputs / 2.3.3 1.1 Random Signals 1 Correlation Analysis and Spectral Density 1.2 Spectral Estimation 8 2.4 Minimum-Phase and 1.3 Signal Modeling 11 System Invertibility 54 1.3.1Rational orPole-Zero 2.4.1 System Invertibility and Models / 1.3.2 Fractional Minimum-Phase Systems / Pole-Zero Models and 2.4.2 All-Pass Systems / 2.4.3 Fractal Models Minimum-Phase and All-Pass 1.4 Adaptive Filtering 16 Decomposition / 2.4.4 Spectral 1.4.1 Applications of Adaptive Factorization Filters / 1.4.2 Features of 2.5 Lattice Filter Realizations 64 Adaptive Filters 2.5.1 All-Zero Lattice Structures / 1.5 Array Processing 25 2.5.2 All-Pole Lattice Structures 1.5.1 Spatial Filtering or 2.6 Summary 70 Beamforming/1.5.2 Adaptive Problems 70 Interference Mitigation in Radar Systems/1.5.3 Adaptive 3 Random Variables,Vectors, Sidelobe Canceler and Sequences 75 1.6 Organization of the Book 29 3.1 Random Variables 75 2 Fundamentals of Discrete- Time Signal Processing 33 3.1.1 Distribution and Density Functions / 3.1.2 Statistical Averages / 3.1.3 Some Useful 2.1 Discrete-Time Signals 33 Random Variables 2.1.1 Continuous-Time,Discrete- 3.2 Random Vectors 83 Time,and Digital Signals / 2.1.2 Mathematical Description of 3.2.1 Definitions and Second-Order Signals / 2.1.3 Real-World Signals Moments / 3.2.2 Linear Transformations of Random 2.2 Transform-Domain Vectors / 3.2.3 Normal Random Representation of Vectors / 3.2.4 Sums of Independent Deterministic Signals 37 Random Variables 2.2.1 Fourier Transforms and 3.3 Discrete-Time Stochastic Fourier Series / 2.2.2 Sampling Processes 97 of Continuous-Time Signals / 2.2.3 The Discrete Fourier 3.3.1 Description Using Transform / 2.2.4 The Probability Functions / 3.3.2 z-Transform / 2.2.5 Representation Second-Order Statistical of Narrowband Signals Description / 3.3.3 Stationarity / x