&lt;title&gt;Information fusion for onboard and offboard avionics&lt;/title&gt;

Kurien, T.; Chao, Alan; Gully, Sol W.; Wood, Richard

doi:10.1117/12.303683

Cited by 1 publication

(1 citation statement)

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“…Sensor fusion is concerned with the interpretation and reconciliation of real-time data received from multiple sensors. The primary applications of such fusion are in military command, control and communications systems [5,4]. Other applications include navigation and traffic control systems [9], weather and earth sciences [8] and process control in industry [17].…”

Section: Data Fusionmentioning

confidence: 99%

Utility-based resolution of data inconsistencies

Motro

Anokhin

Acar

2004

Proceedings of the 2004 International Workshop on Information Quality in Information Systems

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A virtual database system is software that provides unified access to multiple information sources. If the sources are overlapping in their contents and independently maintained, then the likelihood of inconsistent answers is high. Solutions are often based on ranking (which sorts the different answers according to recurrence) and on fusion (which synthesizes a new value from the different alternatives according to a specific formula). In this paper we argue that both methods are flawed, and we offer alternative solutions that are based on knowledge about the performance of the source data; including features such as recentness, availability, accuracy and cost. These features are combined in a flexible utility function that expresses the overall value of a data item to the user. Utility allows us to (1) define meaningful ranking on the inconsistent set of answers, and offer the topranked answer as a preferred answer; (2) determine whether a fusion value is indeed better than the initial values, by calculating its utility and comparing it to the utilities of the initial values; and (3) discover the best fusion: the fusion formula that optimizes the utility. The advantages of such performance-based and utility-driven ranking and fusion are considerable.

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Section: Data Fusionmentioning

confidence: 99%