bullet Sensor and Data Fusion by Lawrence A. Klein

 

 

  Title: Sensor and Data Fusion

  Author: Lawrence A. Klein

  Publisher: SPIE--The International Society for Optical Engineering

  Pubdate: July 2004

  ISBN: 0819454354

 

Editorial Review

 

Sensor and Data Fusion

This book describes the benefits of sensor fusion as illustrated by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance, sensor system application scenarios that may limit sensor size but still require high resolution data, and the attributes of data fusion architectures and algorithms. The data fusion algorithms discussed in detail include classical inference, Bayesian inference, Dempster-Shafer evidential theory, artificial neural networks, voting logic as derived from Boolean algebra expressions, fuzzy logic, and detection and tracking of objects using only passively acquired data. A summary is presented of the information required to implement each of the data fusion algorithms discussed.

 

Weather forecasting, Earth resource surveys that use remote sensing, vehicular traffic management, target classification and tracking, military and homeland defense, and battlefield assessment are some of the applications that will benefit from the discussions of signature-generation phenomena, sensor fusion architectures, and data fusion algorithms provided in this text.

 

   

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