Explores advanced tracking, sensor management, and distributed fusion for modern engineering applications
Advances in statistical signal processing, sensor networks, and control theory have created a need for a unified resource on nonlinear filtering, multitarget tracking, sensor management, and distributed fusion. Advanced Techniques in Tracking and Sensor Management: Theory and Applications offers an overview of the algorithms, frameworks, and applications shaping tracking and sensor research.
Drawing on four decades of research, the book is organized into four parts covering nonlinear filtering, multi-sensor and multitarget tracking, sensor management, and distributed fusion. Topics include particle filtering for constrained systems, random finite set–based multitarget tracking, scheduling and resource allocation, and consensus-based fusion. The book combines theory with applications in radar, surveillance, space situational awareness, and autonomous navigation. Chapters by international experts make complex concepts accessible to engineers, scientists, and graduate students.
Both a graduate-level textbook and a practitioner reference for defense, aerospace, and autonomous systems, this book:
This book is essential reading for graduate courses in statistical signal processing, target tracking, and sensor management in electrical and computer engineering. It is also a valuable resource for engineers and researchers in aerospace, defense, autonomous systems, and surveillance.
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Mahendra Mallick, PhD, is an international expert in filtering, multitarget tracking, and data fusion. A Life Senior Member of the IEEE, he served as an Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and co-edited Integrated Tracking, Classification, and Sensor Management: Theory and Applications.
Ba-Ngu Vo, PhD, is a Professor and Signals & Systems Chair at Curtin University, Australia. He is a Fellow of the IEEE. He was an Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and and IEEE Transactions on Signal Processing. He is currently a Senior Area Editor of IEEE Transactions on Signal Processing. He co-edited Integrated Tracking, Classification, and Sensor Management: Theory and Applications.
Ratnasingham Tharmarasa, PhD, is an Assistant Professor of Electrical and Computer Engineering at McMaster University, Canada. He serves as an Associate Editor of Signal Processing (Elsevier) and specializes in target tracking, sensor management, and data fusion.
Explores advanced tracking, sensor management, and distributed fusion for modern engineering applications
Advances in statistical signal processing, sensor networks, and control theory have created a need for a unified resource on nonlinear filtering, multitarget tracking, sensor management, and distributed fusion. Advanced Techniques in Tracking and Sensor Management: Theory and Applications offers an overview of the algorithms, frameworks, and applications shaping tracking and sensor research.
Drawing on four decades of research, the book is organized into four parts covering nonlinear filtering, multi-sensor and multitarget tracking, sensor management, and distributed fusion. Topics include particle filtering for constrained systems, random finite set–based multitarget tracking, scheduling and resource allocation, and consensus-based fusion. The book combines theory with applications in radar, surveillance, space situational awareness, and autonomous navigation. Chapters by international experts make complex concepts accessible to engineers, scientists, and graduate students.
Both a graduate-level textbook and a practitioner reference for defense, aerospace, and autonomous systems, this book:
This book is essential reading for graduate courses in statistical signal processing, target tracking, and sensor management in electrical and computer engineering. It is also a valuable resource for engineers and researchers in aerospace, defense, autonomous systems, and surveillance.
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