Cognitive Electronic Warfare: An Artificial Intelligence Approach, コグニティブ EW:人工知能によるアプローチ, 9781630818111, 978-1-63081-811-1,「次世代装備」

Cognitive Electronic Warfare: An Artificial Intelligence Approach

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Cognitive Electronic Warfare: An Artificial Intelligence Approach

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書名

Cognitive Electronic Warfare: An Artificial Intelligence Approach
コグニティブ EW:人工知能によるアプローチ
著者・編者 Haigh, K.Z. & Andrusenko, J.
発行元 Artech House
発行年/月 2021年10月   
装丁 Hardcover
ページ数/巻数 288 ページ
ISBN 978-1-63081-811-1
発送予定 海外倉庫よりお取り寄せ 3-4週間以内に発送します
 

Description

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.

 

Contents:

Intro to Cognitive EW
Objective Function
Machine Learning Primer
Electronic Support
Electronic Protect and Electronic Attack
Electronic Battle Management
Real-time In-mission Planning and Learning
Data Management
Architecture
Test and Evaluation