Sensor management is an enabling technology for the next generation of agile, multi-modal, and multi-waveform sensor platforms to efficiently perform tasks such as target detection, tracking, and identification. In sensor management the sequence of sensor actions, such as pointing angle, modality, or waveform, are selected adaptively based on information extracted from past measurements. This book presents the theory of sensor management with applications to real world examples such as adaptive mine detection, adaptive signal and image sampling, multiple target tracking, and radar waveform design. It is written by leading experts in the field for a diverse engineering audience ranging from signal processing, to automatic control, mathematical statistics, and machine learning. The level of treatment of the book is tutorial and self contained. The chapters of the book are grouped into three sections: theoretical foundations; approximate approaches; and applications. The book assumes the reader has a technical background at the level of a first year graduate student in one of the systems engineering disciplines, e.g. signal processing, control, or communications. An appendix is included on topics that the reader may not have seen as a first year graduate student such as: partially observable markov processes, statistical decision theory, information theory, and dynamic programming. TOC:General Overview of active sensing.- Notation and other preliminaries.- Markov decision processes (MDP) formulation and approximation.- Simulation-based approaches and performance approximations.- Other paradigms for active sensor management.- Applications.
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