Paper
18 April 2006 The challenge of scalable and distributed fusion of disparate sources of information
Author Affiliations +
Abstract
A key enabler for Network Centric Warfare (NCW) is a sensor network that can collect and fuse vast amounts of disparate and complementary information from sensors that are geographically dispersed throughout the battlespace. This information will lead to better situation awareness so that commanders will be able to act faster and more effectively. However, these benefits are possible only if the sensor data can be fused and synthesized for distribution to the right user in the right form at the right time within the constraints of available bandwidth. In this paper we consider the problem of developing Level 1 data fusion algorithms for disparate fusion in NCW. These algorithms must be capable of operating in a fully distributed (or decentralized) manner; must be able to scale to extremely large numbers of entities; and must be able to combine many disparate types of data. To meet these needs we propose a framework that consists of three main components: an attribute-based state representation that treats an entity state as a collection of attributes, new methods or interpretations of uncertainty, and robust algorithms for distributed data fusion. We illustrate the discussion in the context of maritime domain awareness, mobile adhoc networks, and multispectral image fusion.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Simon J. Julier, Jeffrey K. Uhlmann, Joshua Walters, Ranjeev Mittu, and Kannappan Palaniappan "The challenge of scalable and distributed fusion of disparate sources of information", Proc. SPIE 6242, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2006, 62420P (18 April 2006); https://doi.org/10.1117/12.666395
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CITATIONS
Cited by 16 scholarly publications.
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KEYWORDS
Data fusion

Sensors

Algorithm development

Information fusion

Copper

Detection and tracking algorithms

Image fusion

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