ABSTRACT
This chapter explores some aspects of the theoretical framework that has been developed to analyze the nature, performance, and fundamental limits for information processing in the context of data fusion. It discusses how Bayesian methods for distributed data fusion can be interpreted from the point of view information theory. In a distributed network of sensors, the sensing system may be comprised of multiple sensors that are physically disjoint or distributed in time or space, and that work cooperatively. Sensor administration has been addressed in the context of wireless networking and not necessarily in conjunction with the unique constraints imposed by data fusion methodologies. The chapter also discusses the approach of using a probabilistic, information processing approach to data fusion in multi-sensor networks. The Bayesian approach was seen to be the central unifying tool in formulating the key concepts and techniques for decentralized organization of information. The chapter examines the connections between information theory and distributed detection.
