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9780387278926

Foundations And Applications of Sensor Management

by ; ; ;
  • ISBN13:

    9780387278926

  • ISBN10:

    0387278923

  • Format: Hardcover
  • Copyright: 2007-12-30
  • Publisher: Springer Verlag

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Summary

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.

Table of Contents

Prefacep. v
Acknowledgmentsp. vii
Contributing Authorsp. xv
Symbol Indexp. xvii
Overview of Bookp. 1
Introductionp. 1
Scope of Bookp. 2
Book Organizationp. 3
Stochastic Control Theory for Sensor Managementp. 7
Introductionp. 7
Markov Decision Problemsp. 10
Partially Observed Markov Decision Problemsp. 19
Approximate Dynamic Programmingp. 26
Examplep. 27
Conclusionp. 32
Information Theoretic Approaches to Sensor Managementp. 33
Introductionp. 33
Backgroundp. 35
Information-Optimal Policy Searchp. 40
Information Gain Via Classification Reductionp. 43
A Near Universal Proxyp. 44
Information Theoretic Sensor Management for Multi-target Trackingp. 47
Terrain Classification in Hyperspectral Satellite Imageryp. 53
Conclusion and Perspectivesp. 57
Joint Multi-target Particle Filteringp. 59
Introductionp. 59
The Joint Multi-target Probability Densityp. 62
Particle Filter Implementation of JMPDp. 71
Multi-target Tracking Experimentsp. 85
Conclusionsp. 91
POMDP Approximation Using Simulation and Heuristicsp. 95
Introductionp. 95
Motivating Examplep. 97
Basic Principle: Q-value Approximationp. 98
Control Architecturep. 101
Q-value Approximation Methodsp. 104
Simulation Resultp. 116
Summary and Discussionp. 118
Multi-armed Bandit Problemsp. 121
Introductionp. 121
The Classical Multi-armed Banditp. 122
Variants of the Multi-armed Bandit Problemp. 134
Examplep. 148
Chapter Summaryp. 151
Application of Multi-armed Bandits to Sensor Managementp. 153
Motivating Application and Overviewp. 153
Application to Sensor Managementp. 155
Example Applicationp. 162
Summary and Discussionp. 173
Active Learning and Samplingp. 177
Introductionp. 177
A Simple One-dimensional Problemp. 179
Beyond 1d - Piecewise Constant Function Estimationp. 190
Final Remarks and Open Questionsp. 199
Plan-in-Advance Learningp. 201
Introductionp. 201
Analytical Forms of the Classifierp. 203
Pre-labeling Selection of Basis Functions [phi]p. 204
Pre-labeling Selection of Data [chi subscript tr]p. 209
Connection to Theory of Optimal Experimentsp. 210
Application to UXO Detectionp. 212
Chapter Summaryp. 219
Sensor Scheduling in Radarp. 221
Introductionp. 221
Basic Radarp. 222
Measurement in Radarp. 233
Basic Scheduling of Waveforms in Target Trackingp. 234
Measures of Effectiveness for Waveformsp. 239
Scheduling of Beam Steering and Waveformsp. 245
Waveform Librariesp. 250
Conclusionp. 255
Defense Applicationsp. 257
Introductionp. 257
Backgroundp. 259
The Contemporary Situationp. 260
Dynamic Tactical Targeting (DTT)p. 262
Conclusionp. 266
Appendicesp. 269
Information Theoryp. 269
Markov Processesp. 273
Stopping Timesp. 278
Referencesp. 283
Indexp. 305
Table of Contents provided by Ingram. All Rights Reserved.

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