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Artech House USA
Essential Principles of Signals Collection and Analysis

Essential Principles of Signals Collection and Analysis

Copyright: 2023
Pages: 300
ISBN: 9781630816902

Hardback $124.00 Qty:
Digital download and online $102.00 Qty:
This book provides a clear and systematic introduction to the basic concepts, foundational mathematics principles, and application of signals collection and supporting technologies. It describes the essential principles of signals collection and analysis for both tactical and commercial applications, and applies the foundational principles and concepts pertaining to the collection and exploitation of uncooperative signals of interest. You will be equipped with the basic concepts and skills necessary to manage and develop signals collection systems, and benefit from the practical, hands-on information you can confidently implement and apply. You will also find abundant references included to guide you further in the areas of signals collection. The book uniquely presents the fundamental mathematics of the collection and processing of signals in a manner easily understood by newcomers to the field, while practitioners will find it to be a practical, go-to desktop reference for signal analysis. This is an ideal, one-of-a-kind text for graduate students, analysts, managers, and others who need a rapid introduction to the diverse and growing field of signals analytics.

Chapter 1: Introduction to Signals Collection and Processing
1 Introduction to Signals Collection and Processing
1.1 Introduction
1.2 Presentation Organization


Chapter 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 WiFi
2.8 Signal Detection
2.9 Conclusion


Chapter 3: Access to RF Signals
3.1 Introduction
3.2 RF Signal Collection Platforms
3.3 Altitude and Shape of Orbits
3.4 Orbital Mechanics
3.5 Conclusion


Chapter 4: Radar Fundamentals
4.1 Introduction
4.2 Electro-Magnetic (EM) Theory
4.3 Antennas
4.4 Radar Equation
4.5 Summary


Chapter 5: Geolocation
5.1 Introduction
5.2 Angle of Arrival Methods
5.3 Time Difference of Arrival (TDOA) Methods
5.4 Frequency Difference of Arrival (FDOA) Methods
5.5 Cross Ambiguity Function (CAF)
5.6 Summary


Chapter 6: Signals Detection and Estimation
6.1 Introduction
6.2 Detection Theory
6.3 Detection of Signals in Noise
6.4 Signal Parameter Estimation
6.5 Summary


Chapter 7: Cryptography Fundamentals
7.1 Introduction
7.2 Mathematical Fundamentals of Cryptography
7.3 Symmetric Cryptography
7.4 Asymmetric Cryptography
7.5 Summary


Chapter 8: Signal Networks
8.1 Introduction
8.2 Internet Protocol Stack
8.3 Types of Packet Delay
8.4 Summary


Chapter 9: Machine Learning for RF Signal Classification
9.1 Introduction
9.3 An Overview of Machine Learning Algorithms
9.4 Deep Neural Networks
9.5 RF Signal Dataset for WiFi Fingerprinting
9.6 Deep Learning Based WiFi Signal Classification
9.7 Conclusion


Chapter 10: Future Trends in Signals Collection and Analysis
10.1 Introduction
10.2 Unmanned Sensors
10.3 Higher Frequency Communication Networks (e.g., 6-G and Beyond)
10.4 Internet of Things (IoT)
10.5 Enhanced AI/ML Applications
10.6 Conclusion

  • Erik P. Blasch

    is a program officer at the United States Air Force Research Laboratory (AFRL) Air Force Office of Scientific Research (AFOSR). He received Ph.D. in electrical engineering from Wright State University. He is a Fellow of IEEE.

  • Uttam K. Majumder is a senior electronics engineer at the United States Air Force Research Laboratory (AFRL). He received his Ph.D. in electrical engineering from Purdue University. He is a senior member of IEEE.
  • David A. Garren

    is a professor at the Naval Postgraduate School. He received his Ph.D. from the College of William and Mary. He is a senior member of IEEE.

© 2024 Artech House