9780819491336-0819491330-Sensor and Data Fusion: A Tool for Information Assessment and Decision Making, Second Edition (SPIE Press Monograph PM222)

Sensor and Data Fusion: A Tool for Information Assessment and Decision Making, Second Edition (SPIE Press Monograph PM222)

ISBN-13: 9780819491336
ISBN-10: 0819491330
Edition: 2nd
Author: Lawrence A. Klein
Publication date: 2012
Publisher: SPIE Press
Format: Hardcover 512 pages
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Book details

ISBN-13: 9780819491336
ISBN-10: 0819491330
Edition: 2nd
Author: Lawrence A. Klein
Publication date: 2012
Publisher: SPIE Press
Format: Hardcover 512 pages

Summary

Acknowledged author Lawrence A. Klein wrote Sensor and Data Fusion: A Tool for Information Assessment and Decision Making, Second Edition (SPIE Press Monograph PM222) comprising 512 pages back in 2012. Textbook and eTextbook are published under ISBN 0819491330 and 9780819491336. Since then Sensor and Data Fusion: A Tool for Information Assessment and Decision Making, Second Edition (SPIE Press Monograph PM222) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

This book illustrates the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance. Topics include applications of multiple-sensor systems; target, background, and atmospheric signature-generation phenomena and modeling; and methods of combining multiple-sensor data in target identity and tracking data fusion architectures. Weather forecasting, Earth resource surveys that use remote sensing, vehicular traffic management, target classification and tracking, military and homeland defense, and battlefield assessment are some of the applications that benefit from the discussions of signature-generation phenomena, sensor fusion architectures, and data fusion algorithms provided in this text.

The information in this edition has been substantially expanded and updated to incorporate recent approaches to sensor and data fusion, as well as application examples. A new chapter about data fusion issues associated with multiple-radar tracking systems has also been added.

Chapter 1. Introduction

Chapter 2. Multiple-Sensor System Applications, Benefits, and Design Considerations

Chapter 3. Sensor and Data Fusion Architectures and Algorithms

Chapter 4. Classical Inference

Chapter 5. Bayesian Inference

Chapter 6. Dempster-Shafer Evidential Theory

Chapter 7. Artificial Neural Networks

Chapter 8. Voting Logic Fusion

Chapter 9. Fuzzy Logic and Fuzzy Neural Networks

Chapter 10. Data Fusion Issues Associated With Multiple-Radar Tracking Systems

Chapter 11. Pasive Data Association Techniques for Unambiguous Location of Targets

Chapter 12. Retrospective Comments

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