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 pressing need for a unified resource that synthesizes the latest developments in nonlinear filtering, multitarget tracking, sensor management, and distributed fusion. Advanced Techniques in Tracking and Sensor Management: Theory and Applications provides a carefully structured overview of the state-of-the-art algorithms, mathematical frameworks, and real-world applications that define the current landscape of tracking and sensor research.
Unifying four decades of research, the book is divided into four parts, each focusing on a central domain: nonlinear filtering, multi-sensor and multitarget tracking, sensor management, and distributed fusion. Topics include particle filtering methods for constrained systems, random finite set-based multitarget tracking, advanced scheduling and resource allocation strategies for sensor management, and consensus-based techniques for distributed fusion. These areas are covered with both theoretical rigor and practical clarity, highlighting their application to radar systems, intelligence and surveillance operations, space situational awareness, and autonomous vehicle navigation. Each in-depth chapter, authored by leading international experts, balances mathematical exposition with illustrative applications to make complex concepts accessible to engineers, scientists, and graduate students.
Both a textbook for advanced study and a reference for practitioners working at the forefront of defense, aerospace, and autonomous systems, Advanced Techniques in Tracking and Sensor Management:
- Features cutting-edge algorithms for space object tracking, space debris detection, and SLAM with finite set statistics
- Provides rigorous treatments of Bayesian filtering and multitarget estimation methods under cluttered, and uncertain environments
- Introduces new approaches to multi-agile satellite scheduling and robust power allocation for MIMO radar systems
- Explores distributed state estimation and multi-object density fusion across sensor networks
Advanced Techniques in Tracking and Sensor Management: Theory and Applications is essential reading for graduate-level courses in statistical signal processing, target tracking, and sensor management within electrical and computer engineering programs. It is also a key reference for engineers and researchers working in aerospace, defense, autonomous systems, and surveillance industries.
About the Author :
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.
