Signals Collection and Estimation from Non-Cooperative Emitters / David A. Garren, Uttam K. Majumder, and Eric Blasch.

Format:

Book

Author/Creator:

Garren, David A., author.

Majumder, Uttam K., author.

Blasch, Eric, author.

Series:

Artech House intelligence and information operations library

Language:

English

Subjects (All):

Electronic surveillance.

Physical Description:

1 online resource (xii, 205 pages) : illustrations, charts.

Edition:

First edition.

Place of Publication:

Norwood, MA : Artech House, [2023]

Summary:

"This book is an introductory text describing the fundamentals of signals collection and processing. This material will equip the graduate student or engineering practitioner with the basic concepts and skills required to manage and develop systems for collecting and processing signals. Key foundations and principles describe the processes of collecting and analyzing signals from an uncooperative source, formulated from physical and signal theoretic concepts. As a technical text, it applies the foundational principles and concepts to the collection and exploitation of uncooperative signals of interest. Finally, it provides references for further study of signals intelligence analysis."--Introduction

Contents:

Intro

Essential Principles of Signals Collection and Analysis

Contents

Foreword

1 Introduction to Signals Collection and Analysis

1.1 Key Foundations

1.2 Presentation Organization

2 RF Signals Classification

2.1 Introduction

2.2 Communication Channels

2.3 RF Signals Analysis

2.4 RF Analog Signals Modulation

2.5 RF Digital Signals Modulation

2.6 RF Shift Keying

2.7 RF Wi-Fi

2.8 RF Signal Detection

2.9 Conclusions

References

4 Radar Fundamentals

4.1 Introduction

4.2 Electromagnetic Theory

4.2.1 Maxwell's Equations

4.2.2 EM Wave Propagation

4.2.3 EM Wave Polarization

4.3 Antennas

4.3.1 Pure Magnetic Dipole Antenna Concept

4.3.2 Transmission and Reception Beam Patterns

4.4 Radar Equation

4.4.1 Signal Power Over One-Way Link

4.4.2 Target Radar Cross Section

4.4.3 EM Power Density for Monostatic Receiver

4.5 Summary

5 Geolocation

5.1 Introduction

5.1.1 Emitter and Collector Assumptions

5.1.2 Possible Vignettes

5.2 Angle of Arrival Methods

5.2.1 Array Model for AoA/DOA Estimation

5.2.2 Array Transfer Vector

5.2.3 Uniform Linear Array for AoA/DoA Estimation

5.3 Time Difference of Arrival Methods

5.3.1 Time of Arrival

5.3.2 Difference of Time of Arrivals

5.3.3 Hyperbolic Isochrones

5.3.4 TDOA Calculation Details

5.4 Frequency Difference of Arrival Methods

5.4.1 Doppler Frequency

5.4.2 Difference of Doppler Frequencies

5.4.3 FDOA Calculation Details

5.5 Cross Ambiguity Function

5.6 Summary

3 Access to RF Signals

3.1 Introduction

3.2 RF Signal Collection Platforms

3.2.1 RF Signal Collection from Ground

3.2.2 RF Signal Collection from Water

3.2.3 RF Signal Collection from Air

3.2.4 RF Signal Collection from Space

3.3 Altitude and Shape of Orbits.

3.3.1 Low-Earth Orbit

3.3.2 Medium-Earth Orbit

3.3.3 High-Earth Orbit

3.3.4 Special Orbit Terminology

3.4 Orbital Mechanics

3.5 Conclusion

6 Signals Detection and Estimation

6.1 Introduction

6.2 Detection Theory

6.2.1 Signal Detection Terminology

6.2.2 Signal Detection Strategy

6.3 Detection of Signals in Noise

6.3.1 Matched Filter

6.3.2 Matched Filter: Correlator and Convolution

6.3.3 White Noise Versus Colored Noise

6.3.4 Detection of Known Signals in White Noise

6.3.5 Detection of Known Signals in Colored Noise

6.3.6 Detection of Random Signals

6.3.7 Detection in Non-Gaussian Noise

6.3.8 Designing Detectors with Unknown Parameters

6.4 Signal Parameter Estimation

6.4.1 Minimum Variance Unbiased Estimation

6.4.2 Cramer-Rao Lower Bound

6.4.3 Maximum Likelihood Estimation

6.4.4 Maximum A Posteriori Estimator

6.5 Summary

7 Cryptography Fundamentals

7.1 Introduction

7.1.1 Connection with Signals Collection

7.1.2 Primary Goals of Cryptography

7.1.3 Primary Algorithm Types

7.2 Mathematical Fundamentals of Cryptography

7.2.1 Modulo Arithmetic

7.2.2 Euler's Totient Function

7.3 Symmetric Cryptography

7.3.1 Model of Symmetric Cryptography

7.3.2 Key Generation and Distribution

7.3.3 Stream Ciphers

7.3.4 Block Ciphers

7.4 Asymmetric Cryptography

7.4.1 Basic Concepts

7.4.2 RSA Algorithm

7.5 Summary

8 Signal Networks

8.1 Introduction

8.1.1 Wired Signals

8.1.2 Wireless Signals

8.2 Protocol Stack

8.2.1 Physical Layer

8.2.2 Data Link Layer

8.2.3 Network Layer

8.2.4 Transport Layer

8.2.5 Application Layer

8.3 Types of Message Delay

8.3.1 Propagation Delay

8.3.2 Transmission Delay

8.3.3 Router Processing Delay

8.3.4 Queuing Delay

8.4 Summary

References.

9 Machine Learning for RF Signal Classification

9.1 Introduction

9.2 RF Signal Classification Problems

9.2.1 RF Feature Learning

9.2.2 Attention and Saliency

9.2.3 Autonomous RF Sensor Configurations

9.2.4 Waveform Synthesis

9.3 An Overview of Machine Learning Algorithms

9.4 Deep Neural Networks

Convolution Layers

Pooling Layers

Fully Connected Layers

DropOut Layer

9.5 RF Signal Dataset for Wi-Fi Fingerprinting

9.6 Deep-Learning-Based Wi-Fi Signal Classification

RF Signal Data Preparation

Deep-Learning Model Preparation

Updated Deep-Learning Model and Training

Results

9.7 Conclusion

10 Future Trends in Signals Collection and Analysis

10.1 Introduction

10.2 Unmanned Sensors

10.3 Higher Frequency Communication Networks: 6G and Beyond

10.4 Internet of Things

10.5 Enhanced AI/ML Applications

10.5.1 Robust and Reliable Classifications for Noisy Signals

10.5.2 Signals Classification Algorithm's Performance Evaluations

10.6 Conclusion

About the Authors

Index.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes bibliographical references and index.

ISBN:

1-63081-691-4