Using MATLAB® examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly for aerospace applications, although the methods can also be applied to systems in other areas, such as biomedicine, military defense, and environmental engineering. After presenting several useful strategies and algorithms for DF and tracking performance, the book evaluates DF algorithms, software, and systems. It next covers fuzzy logic, fuzzy sets and their properties, fuzzy logic operators, fuzzy propositions/rule-based systems, an inference engine, and defuzzification methods. It develops a new MATLAB graphical user interface for evaluating fuzzy implication functions, before using fuzzy logic to estimate the unknown states of a dynamic system by processing sensor data. The book then employs principal component analysis, spatial frequency, and wavelet-based image fusion algorithms for the fusion of image data from sensors. It also presents procedures for combing tracks obtained from imaging sensor and ground-based radar. The final chapters discuss how DF is applied to mobile intelligent autonomous systems and intelligent monitoring systems. Fusing sensors’ data can lead to numerous benefits in a system’s performance. Through real-world examples and the evaluation of algorithmic results, this detailed book provides an understanding of MSDF concepts and methods from a practical point of view. Select MATLAB programs are available for download on www.crcpress.com Contents 8 Preface 20 Acknowledgments 22 Author 24 Contributors 26 Introduction 28 Part I: Theory of Data Fusion and Kinematic-Level Fusion 36 Chapter 1. Introduction 38 Chapter 2. Concepts and Theory of Data Fusion 46 Chapter 3. Strategies and Algorithms for Target Tracking and Data Fusion 98 Chapter 4. Performance Evaluation of Data Fusion Systems, Software, and Tracking 192 Part II: Fuzzy Logic and Decision Fusion 248 Chapter 5. Introduction 250 Chapter 6. Theory of Fuzzy Logic 252 Chapter 7. Decision Fusion 328 Chapter 8. Performance Evaluation of Fuzzy Logic-Based Decision Systems 360 Part III: Pixel- and Feature-Level Image Fusion 390 Chapter 9. Introduction 392 Chapter 10. Pixel- and Feature-Level Image Fusion Concepts and Algorithms 396 Chapter 11. Performance Evaluation of Image-Based Data Fusion Systems 450 Part IV: A Brief on Data Fusion in Other Systems 512 Chapter 12. Introduction: Overview of Data Fusion in Mobile Intelligent Autonomous Systems 514 Chapter 13. Intelligent Monitoring and Fusion 520 Appendix: Numerical, Statistical, and Estimation Methods 530 Index 558 This title explores the theory and concepts of multi-sensor data fusion, including kinematic data fusion, fuzzy logic and decision fusion, and pixel/image-level fusion. It elucidates aspects of data fusion strategies, algorithms, and performance evaluation, mainly for aerospace applications
