Detection and Estimation for Communication and Radar Systems

by Kung Yao, Flavio Lorenzelli, Chiao-En Chen

Overview

Covering the fundamentals of detection and estimation theory, this systematic guide describes statistical tools that can be used to analyze, design, implement and optimize real-world systems. Detailed derivations of the various statistical methods are provided, ensuring a deeper understanding of the basics. Packed with practical insights, it uses extensive examples from communication, telecommunication and radar engineering to illustrate how theoretical results are derived and applied in practice. A unique blend of theory and applications and over 80 analytical and computational end-of-chapter problems make this an ideal resource for both graduate students and professional engineers.

Product Details

ISBN-13:	9781139609760
Publisher:	Cambridge University Press
Publication date:	01/17/2013
Sold by:	Barnes & Noble
Format:	eBook
File size:	24 MB
Note:	This product may take a few minutes to download.

About the Author

Kung Yao is a Distinguished Professor in the Electrical Engineering Department at the University of California, Los Angeles. He received his BS (Highest Honors) and PhD from Princeton University. A Life Fellow of the IEEE, he has worked for or consulted for several leading companies, including AT&T Bell Laboratories, TRW, Hughes Aircraft Company and Raytheon.
Flavio Lorenzelli received his PhD from the University of California, Los Angeles and for several years was with ST Microelectronics. The recipient of a Fulbright fellowship in 1989, he has been an engineer at The Aerospace Corporation since 2007 and is a Lecturer in the Electrical Engineering Department at UCLA.
Chiao-En Chen is an Assistant Professor in both the Department of Electrical Engineering and the Department of Communications Engineering at National Chung Cheng University, Taiwan. He received his PhD from the University of California, Los Angeles in 2008.

Table of Contents

1. Introduction and motivation to detection and estimation; 2. Review of probability and random processes; 3. Statistical hypothesis testing theory; 4. Detection of deterministic binary signals in Gaussian noises; 5. M-ary detection and classification of deterministic signals; 6. Non-coherent detection; 7. Parameter estimation; 8. Analytical and simulation methods for system performance analysis and design.