Originally published in 1968, Harry Van Trees’s Detection, Estimation, and Modulation Theory, Part I is one of the great time-tested classics in the field of signal processing. Highly readable and practically organized, it is as imperative today for professionals, researchers, and students in optimum signal processing as it was over thirty years ago. The second edition is a thorough revision and expansion almost doubling the size of the first edition and accounting for the new developments thus making it again the most comprehensive and up-to-date treatment of the subject. With a wide range of applications such as radar, sonar, communications, seismology, biomedical engineering, and radar astronomy, among others, the important field of detection and estimation has rarely been given such expert treatment as it is here. Each chapter includes section summaries, realistic examples, and a large number of challenging problems that provide excellent study material. This volume which is Part I of a set of four volumes is the most important and widely used textbook and professional reference in the field.

* Paperback reprint of one of the most respected classics in the history of engineering publication * Together with the reprint of Part I and the new Part IV, this will be the most complete treatment of the subject available * Provides a highly-readable discussion of Signal Processing and Noise * Features numerous problems and illustrations to help promote understanding of the topics * Contents are highly applicable to current systems

Signal processing plays an important role in many diverse application areas, including radar, sonar, communications, seismology, radio astronomy, tomography, and communications. Now, by popular demand, acclaimed author Harry Van Trees' four-part encyclopedic treatment of signal processing is now collected into a set offering 25 years of information in a single source.

"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.