Sensor and data fusion concepts and applications

著者

    • Klein, Lawrence A.

書誌事項

Sensor and data fusion concepts and applications

Lawrence A. Klein

（Tutorial texts in optical engineering, v. TT 35）

SPIE, c1999

2nd ed

  • :pbk

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

First published in 1993, this "Tutorial Text" has been revised and updated to provide explanations and examples of data fusion algorithms in areas not covered in the first edition. These include Bayesian inference, artificial neural networks and fuzzy logic. All of the chapters in the first edition have been revised and updated and new material is included on the FASCODE and MODTRAN atmospheric models, and EOSAEL, which analyzes physical processes that affect the performance of millimeter-wave and IR sensors.

目次

  • Multiple Sensor System Applications, Benefits, and Atmospheric Attenuation
  • Data Fusion Algorithms and Architectures
  • Bayesian Inference
  • Dempster-Shafer Algorithm
  • Artificial Neural Networks
  • Voting Fusion
  • Fuzzy Logic and Neural Networks
  • Passive Data Association Techniques for Unambiguous Location of Targets. Appendices: Planck Radiation Law and Radiative Transfer
  • Voting Fusion With Nested Confidence Levels.

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