1st Edition

Multi-Sensor Data Fusion with MATLAB®

By Jitendra R. Raol Copyright 2009
    568 Pages 224 B/W Illustrations
    by CRC Press

    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

    Theory of Data Fusion and Kinematic-Level Fusion, J.R. Raol, G. Girija, and N. Shanthakumar


    Concepts and Theory of Data Fusion

    Strategies and Algorithms for Target Tracking and Data Fusion

    Performance Evaluation of Data Fusion Systems, Software, and Tracking

    Fuzzy Logic and Decision Fusion, J.R. Raol and S.K. Kashyap


    Theory of Fuzzy Logic

    Decision Fusion

    Performance Evaluation of Fuzzy Logic-Based Decision Systems

    Pixel and Feature-Level Image Fusion, J.R. Raol and V.P.S. Naidu


    Pixel- and Feature-Level Image Fusion Concepts and Algorithms

    Performance Evaluation of Image-Based Data Fusion Systems

    A Brief on Data Fusion in Other Systems, Ajith Gopal and Simukai Utete

    Introduction: Overview of Data Fusion in Mobile Intelligent Autonomous Systems

    Intelligent Monitoring and Fusion




    Jitendra R. Raol is Professor Emeritus at M S Ramaiah Institute of Technology (MSRIT) in Bangalore, India.