Fuzzy logic approach to vulnerability assessment

Kirk A. Dunkelberger

doi:10.1117/12.211813

13 June 1995 Fuzzy logic approach to vulnerability assessment

Kirk A. Dunkelberger

Proceedings Volume 2493, Applications of Fuzzy Logic Technology II; (1995) https://doi.org/10.1117/12.211813
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

Within the context of our sensor fusion systems, we define an entity's vulnerability as the certainty with which other entities have the capability to detect and/or strike the entity; vulnerability assessment (VA) is the inference of vulnerability certainties. This investigation considers two issues: the feasibility of a fuzzy VA algorithm and the interface of a fuzzy VA algorithm into an existing sensor fusion system, including human-machine interface aspects. Relative kinematics, sensor/weapon technical capabilities, sensor/weapon system state, contextual electronic signatures, physics, terrain, atmospherics, and doctrinal bias are certainly all viable inputs to a VA algorithm. These data are traditionally characterized by a mix of continuous, discrete, and/or symbolic values with associated error bounds in various mathematical forms. Hence, the algorithmic infusion of a fuzzy VA into this systemic environment implies resolving the uncertainty information content of these representations and integrating them into a coherent fuzzy reasoning context. The information overload facing the tactical operator has necessitated the reduction of many data to prioritized simple alerts. While there is a reasonable understanding of the visual representations and implications of thresholding probabilistic data, the presentation and thresholding of fuzzy data is not well understood; some of the more critical implications on the human-machine interface are presented herein.

Citation Download Citation

Kirk A. Dunkelberger "Fuzzy logic approach to vulnerability assessment", Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); https://doi.org/10.1117/12.211813

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KEYWORDS

Fuzzy logic

Human-machine interfaces

Sensors

Kinematics

Sensor fusion

Detection and tracking algorithms

Fuzzy systems

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