Multisensor data fusion or distributed sensing, is a relatively new engineering discipline used to combine data from multiple and diverse sensors and sources in order to make inferences about events, activities, and situations. These systems are often compared to the human cognitive process where the brain fuses sensory information from the various sensory organs, evaluates situations, makes decisions, and directs action.

Data fusion technology has been applied most prominently to military applications such as battlefield surveillance and tactical situation assessment. Data fusion has also emerged in commercial applications such as robotics, manufacturing, medical diagnosis, and remote sensing.

The application of data fusion in technical systems requires mathematical and heuristic techniques from fields such as statistics, artificial intelligence, operations research, digital signal processing, pattern recognition, cognitive psychology, information theory and decision theory.

In a typical military command and control (C2) system, data fusion sensors are used to observe electromagnetic radiation, acoustic and thermal energy, nuclear particles, infrared radiation, noise and other signals. Multisensor data fusion provides an important functional framework for building next generation information fusion and cyberspace situational awareness systems.

There exist significant opportunities and numerous technical challenges for the commercial application of data fusion theory into the art and science of modern decision support systems. This handbook provides the absolute best possible overview of the art and science of multisensor data fusion technology.

Congratulations to David Hall and James Llinas for great editorial work on this handbook. I strongly recommend this book to anyone working in this wonderful and rapidly evolving field.