This comprehensive book gives an overview of how cognitive systems and artificial intelligence (AI) can be used in electronic warfare (EW). Readers will learn how EW systems respond more quickly and effectively to battlefield conditions where sophisticated radars and spectrum congestion put a high priority on EW systems that can characterize and classify novel waveforms, discern intent, and devise and test countermeasures. Specific techniques are covered for optimizing a cognitive EW system as well as evaluating its ability to learn new information in real time. The book presents AI for electronic support (ES), including characterization, classification, patterns of life, and intent recognition. Optimization techniques, including temporal tradeoffs and distributed optimization challenges are also discussed. The issues concerning real-time in-mission machine learning and suggests some approaches to address this important challenge are presented and described. The book covers electronic battle management, data management, and knowledge sharing. Evaluation approaches, including how to show that a machine learning system can learn how to handle novel environments, are also discussed. Written by experts with first-hand experience in AI-based EW, this is the first book on in-mission real-time learning and optimization.

This comprehensive book gives an overview of how cognitive systems and artificial intelligence (AI) can be used in electronic warfare (EW). Readers will learn how EW systems respond more quickly and effectively to battlefield conditions where sophisticated radars and spectrum congestion put a high priority on EW systems that can characterize and classify novel waveforms, discern intent, and devise and test countermeasures. Specific techniques are covered for optimizing a cognitive EW system as well as evaluating its ability to learn new information in real time. The book presents AI for electronic support (ES), including characterization, classification, patterns of life, and intent recognition. Optimization techniques, including temporal tradeoffs and distributed optimization challenges are also discussed. The issues concerning real-time in-mission machine learning and suggests some approaches to address this important challenge are presented and described. The book covers electronic battle management, data management, and knowledge sharing. Evaluation approaches, including how to show that a machine learning system can learn how to handle novel environments, are also discussed. Written by experts with first-hand experience in AI-based EW, this is the first book on in-mission real-time learning and optimization.

Electronic warfare is a critical component of modern military operations and has undergone significant advances in recent years. This book provides an overview of electronic warfare, its historical development, key components, and its role in contemporary conflict scenarios. It also discusses emerging trends and challenges in electronic warfare and its contemporary relevance in an era of advanced technology and cyber threats, emphasizing the need for continued research and development in this area. The book explores the burgeoning intersection of artificial intelligence and electronic warfare, highlighting the evolving landscape of modern conflicts and the implications of integrating advanced technologies. The multifaceted roles of artificial intelligence in electronic warfare are highlighted, examining its potential advantages, ethical considerations, and challenges associated with its integration. CONTENTS: Abstract Abbreviations Introduction - Electronic warfare - - Definitions - - Historical development - - The key components - - - Electronic attack (EA) - - - Electronic protection - - - Electronic support - Techniques and tactics - EW systems - - Radar - Relationship of EW to other combat capabilities - - Cyber electronic warfare - The main competitors - - US - - China - - Russia - - NATO - - European Union - Challenges and trends - Asymmetric warfare Artificial intelligence - The historical background of electronic warfare - The role of artificial intelligence in electronic warfare - - Specific applications - AI techniques - - Machine learning - - Fuzzy systems - - Genetic algorithm - Trends - Challenges and risks - - Ethical considerations - Cognitive EW Conclusion Bibliography DOI: 10.58679/MM14430

Since its creation at the beginning of World II, radars have forever transformed the practice of modern warfare. The evolution of countermeasure conducted by electronic warfare systems against radars and radars’ corresponding counter countermeasures is an intriguing technical subject. This book provides a very accessible introduction to a broad range of radar and electronic warfare technologies. The subjects covered in this book range from early radar development to later technologies such as stealthy techniques, low probability of intercept radar, and machine learning. Historical events are used to illustrate the principles of electronic warfare and to help readers to apprehend contexts under which radars and corresponding electronic warfare techniques were developed.

Here's an advanced practitioner's guide to the latest concepts and threats associated with modern electronic warfare (EW). This new book identifies and explains the newest radar and communications threats, and provides EW and radar engineers, managers, and technical professionals with practical, "how-to" information on designing and implementing ECM and ECCM systems.

This book presents a unique and comprehensive introduction to performance prediction of directed energy (DE) systems using mathematical modeling frameworks, with focus on high power radio frequency and high energy laser performance. It provides system designers with a means for predicting DE system performance and measuring the required power levels necessary to neutralize targets including UAVs and other unmanned swarms. The book begins with a systematic and concise overview of DE systems, including its historical roots. You will then learn how to develop effective mathematical models and understand how to use these models to implement safer and efficient use of DE systems in various scenarios. A special section is devoted to examples and attributes of unmanned systems since these are viewed as primary targets suitably disabled by DE systems. There is also an extensive survey of the relevant tools of mathematics and physics for DE systems, together with a series of pertinent references you can follow for further information. The final section of the book outlines potential future research directions that interested researchers are encouraged to pursue. With its exclusive and unmatched coverage of predictive modeling for DE systems and performance, this is an important book for engineers and operators working in the defense industry, including government and private contractors, as well as research practitioners at universities and engineering organizations worldwide working in the field of DE system performance.