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.
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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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. 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 multitarget angleonly tracking, and multisensor 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 multisensor data fusion area. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781032904368
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Hardcover. Etat : new. Hardcover. 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 multitarget angleonly tracking, and multisensor 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 multisensor data fusion area. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032904368
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