Author Description

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 und