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Originally published in 1968, Harry Van Trees’s Detection,Estimation, and Modulation Theory, Part I is one of the greattime-tested classics in the field of signal processing. Highlyreadable and practically organized, it is as imperative today forprofessionals, researchers, and students in optimum signalprocessing as it was over thirty years ago. The second edition is athorough revision and expansion almost doubling the size of thefirst edition and accounting for the new developments thus makingit again the most comprehensive and up-to-date treatment of thesubject.
With a wide range of applications such as radar, sonar,communications, seismology, biomedical engineering, and radarastronomy, among others, the important field of detection andestimation has rarely been given such expert treatment as it ishere. Each chapter includes section summaries, realistic examples,and a large number of challenging problems that provide excellentstudy material. This volume which is Part I of a set of fourvolumes is the most important and widely used textbook andprofessional reference in the field.
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"Since 1968 and after 30 printings of the first edition, Part Iof DEMT has been the textbook for the two generations of studentsand researchers that have designed the signal processing in many ofour operational systems. The Second Edition includessubsequent advances, retains clarity of explanation, and promisesto be the text and reference for future generations."
— Dr. Arthur B. Baggeroer, Ford Professor Emeritus, MIT
The First Edition of Detection, Estimation, and ModulationTheory, Part I, enjoyed a long useful life. However, in theforty-four years since its publication, there have been a largenumber of changes:
The Second Edition is a significant expansion of thefirst edition with 450 pages of new material. Chapter 2 in theFirst Edition, Classical Detection and Estimation Theory, isexpanded into four chapters. Many more examples are developed indetail to enhance readability, and more non-Gaussian models areincluded. A large number of significant developments that areappropriate for an introductory text—including global Bayesianbounds, efficient computational algorithms, equivalent estimationalgorithms, sequential estimation, and importance sampling—areadded. The Fisher and Bayesian linear Gaussian models are studiedin more detail. The First Edition emphasized continuous-timerandom processes. The Second Edition includes acomprehensive development of linear estimation of discrete-timerandom processes leading to discrete-time Wiener and Kalmanfilters. A brief introduction to Bayesian estimation ofnon-Gaussian processes is included. An expanded version of materialfrom Part III develops optimum detectors for continuous-time anddiscrete-time random processes that can be implemented using Wieneror Kalman filters.
As imperative today as it has been since its originalpublication in 1968, this work is sure to remain the leadingreference for engineers who need to apply detection and estimationtheory in diverse systems.About the Author:
HARRY L. VAN TREES, ScD., received his BSc. from theUnited States Military Academy and his ScD. from MassachusettsInstitute of Technology. During his fourteen years as a Professorof Electrical Engineering at MIT, he wrote Parts I, II, and III ofthe DEMT series. On loan from MIT, he served in four senior DoDpositions including Chief Scientist of the U.S. Air Force andPrincipal Deputy Assistant Secretary of Defense (C3I). Returning toacademia as an endowed professor at George Mason University, hefounded the C3I Center and published Part IV of the DEMT series,Optimum Array Processing. He is currently a UniversityProfessor Emeritus.
KRISTINE L. BELL, PhD, is a Senior Scientist at Metron,Inc., and an affiliate faculty member in the Statistics Departmentat George Mason University. She coedited with Dr. Van Trees theWiley-IEEE book Bayesian Bounds for Parameter Estimation andNonlinear Filtering/Tracking.
ZHI TIAN, PhD, is a Professor of Electrical and ComputerEngineering at Michigan Technological University. She is a Fellowof the IEEE.
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