ABSTRACT

With the recent proliferation of service-oriented architectures (SOA), cloud computing technologies, and distributed-interconnected systems, distributed fusion is taking on a larger role in a variety of applications—from environmental monitoring and crisis management to intelligent buildings and defense. Drawing on the work of leading experts around the world, Distributed Data Fusion for Network-Centric Operations examines the state of the art of data fusion in a distributed sensing, communications, and computing environment.

Get Insight into Designing and Implementing Data Fusion in a Distributed Network

Addressing the entirety of information fusion, the contributors cover everything from signal and image processing, through estimation, to situation awareness. In particular, the work offers a timely look at the issues and solutions involving fusion within a distributed network enterprise. These include critical design problems, such as how to maintain a pedigree of agents or nodes that receive information, provide their contribution to the dataset, and pass to other network components. The book also tackles dynamic data sharing within a network-centric enterprise, distributed fusion effects on state estimation, graph-theoretic methods to optimize fusion performance, human engineering factors, and computer ontologies for higher levels of situation assessment.

A comprehensive introduction to this emerging field and its challenges, the book explores how data fusion can be used within grid, distributed, and cloud computing architectures. Bringing together both theoretical and applied research perspectives, this is a valuable reference for fusion researchers and practitioners. It offers guidance and insight for those working on the complex issues of designing and implementing distributed, decentralized information fusion.

chapter 2|29 pages

Distributed Data Fusion

Overarching Design Concerns and Some New Approaches

chapter 3|18 pages

Network-Centric Concepts

Impacts to Distributed Fusion System Design

chapter 6|36 pages

Essence of Distributed Target Tracking

Track Fusion and Track Association

chapter 7|37 pages

Decentralized Data Fusion

Formulation and Algorithms

chapter 9|26 pages

Nonmyopic Sensor Management

chapter 10|24 pages

A Framework for Distributed

Edited BySubrata Das

chapter 14|14 pages

Nonmyopic Sensor Management