This invaluable reference offers the most comprehensive introduction available to the concepts of multisensor data fusion. It introduces key algorithms, provides advice on their utilization, and raises issues associated with their implementation. With a diverse set of mathematical and heuristic techniques for combining data from multiple sources, the book shows how to implement a data fusion system, describes the process for algorithm selection, functional architectures and requirements for ancillary software, and illustrates man-machine interface requirements an database issues.
Inhaltsverzeichnis
Introduction to multisensor data fusion; sensors and sensor data - data inputs; the inference hierarchy; a taxonomy of data fusion techniques; data association; positional fusion; identity declaration and pattern recognition; identity fusion; knowledge based approaches; implementation of data fusion systems.
