Paper
17 May 2006 Evaluation of hybrid fusion 2+ approach for providing air-to-air situational awareness and threat assessment
Kangjin David Lee, Eric Wiesenfeld, Mike Colony
Author Affiliations +
Abstract
Modern combat aircraft pilots increasingly rely on high-level fusion models (JDL Levels 2/3) to provide real-time engagement support in hostile situations. These models provide both Situational Awareness (SA) and Threat Assessment (TA) based on data and the relationships between the data. This information represents two distinct classes of uncertainty: vagueness and ambiguity. To address the needs associated with modeling both of these types of data uncertainty, an innovative hybrid approach was recently introduced, combining probability theory and possibility theory into a unified computational framework. The goal of this research is to qualitatively and quantitatively address the advantages and disadvantages of adopting this hybrid framework as well as identifying instances in which the combined model outperforms or is more appropriate than more classical inference approaches. To accomplish this task, domain specific models will be developed using different theoretical approaches and conventions, and then evaluated in comparison to situational ground truth to determine their accuracy and fidelity. Additionally, the performance tradeoff between accuracy and complexity will be examined in terms of computational cost to determine both the advantages and disadvantages of each approach.
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Kangjin David Lee, Eric Wiesenfeld, and Mike Colony "Evaluation of hybrid fusion 2+ approach for providing air-to-air situational awareness and threat assessment", Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 623512 (17 May 2006); https://doi.org/10.1117/12.664926
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Cited by 1 scholarly publication.
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KEYWORDS
Fuzzy logic

Data modeling

Fuzzy systems

Bayesian inference

Binary data

Systems modeling

Probability theory

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