Foundations and Applications of Sensor Management
Publisher: Springer - To appear late 2007
Editors:
A. Hero, D. Castanon, D. Cochran, K. Kastella
Description 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 follow a logical development from
theoretical foundations to approximate approaches and ending with
applications. The coverage includes the following topics:
stochastic control foundations of sensor management; multi-armed
bandits approaches to sensor management; information theoretic
approaches; managed sensing for multiple target tracking;
approximation methods based on embedded simulation; active learning
for classification and sampling; and sensor scheduling for radar. 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: markov decision processes, information
theory; and stopping times.
Ordering information
The book is scheduled to come out in November 2007. You can place an
order for the book at the Springer website
(link to Springer) .
Alternatively, you can contact Springer at
the following:
Tel: 800-777-4643
Tel: +1 212 460 1500
(Weekdays 8:30am-5:30pm ET)
service-ny@springer.com
Co-authors
Doron Blatt - DRW Holdings
David Castanon - BU
Rui Castro - UWisconsin
Larry Carin - Duke
Edwin Chong - CSU
Doug Cochran - ASU
Stephen Howard - DSTO
Keith Kastella - GD-AIS
Chris Kreucher - GD-AIS
Al Hero - UMichigan
Xuejun Liao - Duke
Aditya Mahajan - UMichigan
Mark Morelande - UMelbourne
Bill Moran - UMelbourne
Rob Nowak - UWisconsin
Bob Washburn - Parietal Systems
Sofia Suvorova - UMelbourne
Demos Teneketzis - UMichigan
Stan Musick - AFRL
Yan Zhang - Humana
Table of contents
i. Preface
ii. Symbol index
1. Overview of Book
2. Stochastic Control for Sensor Management
3. Information Theoretic Approaches
4. Joint Multi-Target Particle Filtering
5. POMDP Approximations using Simulation and Heuristics
6. Multi-Armed Bandit Problems
7. Applications of Multi-Armed Bandits to Sensor Management
8. Active Learning and Sampling
9. Plan-in Advance Learning
10. Sensor Scheduling in Radar
11. Defense Applications
Appendices
Bibliography
Subject index