Ebook: Sensor and Data Fusion - A Tool for Information Assessment and Decision Making

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. Applications that benefit from this technology include: vehicular traffic management, remote sensing, target classification and tracking, weather forecasting, military and homeland defense. Covering data fusion algorithms in detail, the author includes a summary of the information required to implement each of the algorithms discussed, and outlines system application scenarios that may limit sensor size but that require high resolution data.
Content:
Front Matter
• List of Figures
• List of Tables
• Preface
• Table of Contents
• 1. Introduction
2. Multiple Sensor System Applications, Benefits, and Design Considerations
3. Data Fusion Algorithms and Architectures
4. Classical Inference
5. Bayesian Inference
6. Dempster-Shafer Evidential Theory
7. Artificial Neural Networks
8. Voting Logic Fusion
9. Fuzzy Logic and Fuzzy Neural Networks
10. Passive Data Association Techniques for Unambiguous Location of Targets
• 11. Retrospective Comments
Appendices
Index
• About the Author