Data Fusion Mathematics

Theory and Practice
2. Auflage 2025
ISBN: 978-1-032-90436-8
Verlag: Taylor & Francis Ltd

Buch, Englisch, 664 Seiten, Format (B × H): 156 mm x 234 mm

Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF.

This new edition offers updated chapters alongside four new chapters that are based on recent research carried out by the authors, including topics on machine learning techniques, target localization using a network of 2D ground radar, thermal imaging sensors for multi-target angle-only tracking, and multi-sensor data fusion for a single platform and team platforms. This book also covers major mathematical expressions, formulae and equations, and, where feasible, their derivations. It discusses signed distance function concepts, DF models and architectures, aspects and methods of types 1 and 2 fuzzy logics, and related practical applications. In addition, the authors cover soft computing paradigms that are finding increasing applications in multi-sensory DF approaches and applications.

This text is geared toward researchers, scientists, teachers, and practicing engineers interested in and working in the multi-sensor data fusion area.

Zielgruppe

Professional Practice & Development

Autoren/Hrsg.

Sanketh, Ailneni

Raol, Jitendra R.

Selvi, S. Sethu

Kashyap, Sudesh K.

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau Mechatronik, Mikrosysteme (MEMS), Nanosysteme
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Sensorik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Technische Wissenschaften Bauingenieurwesen Bauingenieurwesen
• Technische Wissenschaften Technik Allgemein Nanotechnologie

Inhaltsverzeichnis

1. Introduction to Data Fusion Process. 2. Statistics, Probability Models, and Reliability: Towards Probabilistic Data Fusion. 3. Fuzzy Logic and Possibility Theory Based Fusion. 4. Filtering, Target-Tracking, and Kinematic Data Fusion. 5. Decentralized Data Fusion Systems. 6. Component Analysis and Data Fusion. 7. Image Algebra and Image Fusion. 8. Decision Theory and Fusion. 9. Wireless Sensor Networks and Multimodal Data Fusion. 10. Soft Computing Approaches to Data Fusion. 11. Machine Learning in Data Fusion. 12. Target Localization Using Network of 2D Ground Radars. 13. Multi-Target Angle Only Tracking Using Thermal Imaging Sensors. 14. Multi-Sensor Data Fusion for Single Platform and Team of Platforms.

Über Autor(innen)

Jitendra R. Raol earned a BE and an ME in electrical engineering at M. S. University (MSU) of Baroda, Vadodara, in 1971 and 1973, respectively, and a PhD in electrical and computer engineering at McMaster University, Hamilton, Canada, in 1986. At both places, he was also a postgraduate research and teaching assistant. He joined the National Aeronautical Laboratory (NAL, Bangalore) in 1975. At CSIR-NAL, he was involved in the activities on human pilot modeling in fix- and motion-based research flight simulators. He re-joined NAL in 1986 and retired in July 2007 as Scientist-G and Head of the flight mechanics and control division at CSIR-NAL. His main research interests include data fusion, system identification, state/ parameter estimation, flight mechanics–flight data analysis, H-infinity filtering, non-linear filtering, artificial neural networks, fuzzy logic systems, genetic algorithms, and soft technologies for robotics.

S. Sethu Selvi is a Professor in the Electronics and Communication Engineering Department, Ramaiah Institute of Technology. She earned a PhD in image compression at the Indian Institute of Science in 2001 under Prof. Anamitra Makur. She earned a BE at Thiagarajar College of Engineering, Madurai, in 1992, and an ME at Anna University in 1994. She joined the faculty of the Department of Electronics and Communication at Ramaiah Institute of Technology, Bangalore, in 2002 as an assistant professor. She was promoted to the professor cadre in 2007 and also was the Head of the department from 2008 to 2021. Her fields of interest include digital image processing, machine and deep learning, video processing, character recognition, and biometrics.

Sudesh K. Kashyap is a Chief Scientist and Group Head of the System Identification and Data Fusion Group at the Flight Mechanics and Control Division of CSIR-NAL, Bangalore. He earned a BE in electronics, an ME in electrical engineering, and a PhD in electrical engineering and electronics. Dr. Kashyap was a key member of various projects sponsored by different DRDO labs for the design, development, and evaluation of advanced algorithms for multi-sensor multi-target tracking and fusion for air defense applications such as Real Time Flight Safety Expert System (RTFLEX) and RF Seekers-based tracking of homing targets. His core expertise is in the area of Kalman filtering, multi-sensor data fusion, gating and data association, and target tracking with evasive maneuvers. He has also contributed to a concept proving Fuzzy-Bayesian-based expert system to assist pilots by providing enhanced situational awareness and threat levels in beyond-visual-range (BVR) air-to-air combat scenarios.

Ailneni Sanketh earned a bachelor’s degree in technology at the Jawaharlal Nehru Technological University in Hyderabad and a master’s in technology at the Academy of Scientific and Innovative Research (AcSIR), Bangalore. His specializations include estimation theory and its application to inertial navigation using MEMS sensors. In 2012, he began a professional career as a Scientist at the Flight Mechanics and Controls Division (FMCD) at CSIR-NAL. He is currently pursuing a PhD in the Aerospace Engineering Department of the Indian Institute of Technology (IIT-Madras). His research interests include multi-sensor target tracking, multi-sensor data fusion, navigation, and flight dynamics of unmanned aerial vehicles.