Detection Theory

Applications and Digital Signal Processing

Ralph D. Hippenstiel

• Publisher: CRC Press
• Year: 2017
• eBook ISBN: 9781351835947
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

Using simplified notation and a practical approach, Detection Theory: Applications and Digital Signal Processing introduces the principles of detection theory, the necessary mathematics, and basic signal processing methods along with some recently developed statistical techniques. Throughout the book, the author keeps the needs of practicing engineers firmly in mind. His presentation and choice of topics allows students to quickly become familiar with the detection and signal processing fields and move on to more advanced study and practice. The author also presents many applications and wide-ranging examples that demonstrate how to apply the concepts to real-world problems.

Chapter 1

Introduction

1.1 General Philosophy

In the age of modern warfare the theory of detection and estimation has become a very important topic. The development of radar, sonar, digital communications, and digital signal processing has immensely stimulated these areas. With the advent of the flying machine, which can deliver ordinance to any point at any time, early detection has become essential. The roots of modern detection theory can be found in the desire to protect valuable resources by detecting and destroying enemy airplanes and missiles under all types of environmental conditions. A large body of detection-related articles and books can be found in the statistics area. Hypothesis testing relates to a topic that historically deals with statistics. This statistics topic focuses on the detection and/or estimation of certain phenomena and usually includes the computation of the errors associated with these procedures.

World War II has a rich warfare history that demonstrates the importance of detecting enemy attacks reasonably early to allow for countermeasures or at least for some evasive action. Detection must be sufficiently early to minimize the loss of life. Of course, to obtain a timely warning, early detection is essential and hence, detection must usually be accomplished at very low signal-to-noise ratios (SNRs). In recent history, the development of nuclear, chemical, and biological armament and the many covert ways of delivering this type of ordinance have made detection even more important. For example, it is relatively easy to hide a submarine, a potential missile deployment system, in the ocean. Passive and active sonar systems allow the detection, identification, and localization of submerged platforms. Another example is the ballistic missile system that can be hidden in movable containers. Ballistic missiles, for example the scud missile in the conflict with Iraq, can be detected by radar, optical or imaging systems.

In each one of these scenarios, automated detection allows scanning of large data sets for the purpose of detecting, localizing, and identifying particular targets of interest. We realize, if there is no distortion (i.e., no noise or interference) when observing data then one can readily deduce the presence (or absence), and when appropriate, the type of the signal emitter....

Table of contents

• Cover Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Author
• 1 Introduction
• 2 Review of Deterministic and Random System and Signal Concepts
• 3 Introduction to Signal Processing
• 4 Hypothesis Testing
• 5 Non-Parametric and Sequential Likelihood Ratio Detectors
• 6 Detection of Dynamic Signals in White Gaussian Noise
• 7 Detection of Signals in Colored Gaussian Noise
• 8 Estimation
• 9 Applications to Detection, Parameter Estimation, and Classification
• Appendix A Probability, Random Processes, and Systems
• Appendix B Signals and Transforms
• Appendix C Mathematical Structures
• Appendix D Some Mathematical Expressions and Moments of Probability Density Function
• Appendix E Wavelet Transforms
• Index