Multi-Sensor Data Fusion
An Introduction
1st Edition
Published on 13. July 2007
XIV, 282 pages
978-3-540-71559-7 (ISBN)
Description
The purpose of this book is to provide an introduction to the theories and techniques of multi-sensor data fusion. The book has been designed as a text for a one-semester graduate course in multi-sensor data fusion. It should also be useful to advanced undergraduates in electrical engineering or computer science who are studying data fusion for the ?rst time and to practising en- neers who wish to apply the concepts of data fusion to practical applications. The book is intended to be largely self-contained in so far as the subject of multi-sensor data fusion is concerned, although some prior exposure to the subject may be helpful to the reader. A clear understanding of multi-sensor data fusion can only be achieved with the use of a certain minimum level of mathematics.Itisthereforeassumedthatthereaderhasareasonableworking knowledge of the basic tools of linear algebra, calculus and simple probability theory. More speci?c results and techniques which are required are explained in the body of the book or in appendices which are appended to the end of the book.
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07/2007
1st Edition
Springer
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Content
Basics.- Sensors.- Architecture.- Representation.- Common Representational Format.- Spatial Alignment.- Temporal Alignment.- Sensor Value Normalization.- Data Fusion.- Bayesian Inference.- Parameter Estimation.- Robust Statistics.- Sequential Bayesian Inference.- Bayesian Decision Theory.- Ensemble Learning.- Sensor Management.- Sensor Management.- Appendices.- Software Sources.- Sensor Management.
